What we are reading Volume 2 - blog.abakkusinvest.com

What we are reading ndash Volume 2002

India Strategy

- ICICI Securities

Uttar Pradesh-Breaking free from the shackles of lsquoBIMARUrsquo tag

- Spark Capital

Update on how is GST progressing

- Edelweiss

Cheap data driving profound changes

- Neelkanth Mishra

The Value of lsquoOvervaluedrsquo Stocks

- Outlook Business

This investor rivals Warren Buffett and you probably havenrsquot heard of him

- Market Watch

Global Macro Mid-Year Outlook

-Morgan Stanley

The Psychology of Money

- The Collaborative Fund

Please refer to important disclosures at the end of this report

`

Equity Research May 29 2018

Nifty 50 10633

ICICI Securities Limited is the author and distributor of this report

Cashless status report Cash is back CIC at 116 of GDP (18-Mayrsquo18) ndash back in range

Cashless transactions (ex-RTGS) continue to rise

Previous report ldquoTez-i in digital paymentsrdquo

Strategy

Cashless transactions continue their uptrendhellip so does cash in circulation

116

4

6

8

10

12

14

Jan

11

May 1

1

Se

p 1

1

Jan

12

May 1

2

Se

p 1

2

Jan

13

May 1

3

Se

p 1

3

Jan

14

May 1

4

Se

p 1

4

Jan

15

May 1

5

Se

p 1

5

Jan

16

May 1

6

Se

p 1

6

Jan

17

May 1

7

Se

p 1

7

Jan

18

May 1

8

CIC as a of GDP

0

200

400

600

800

1000

1200

1400

1600

Ap

r1

1

Se

p1

1

Feb1

2

Jul1

2

Dec1

2

May1

3

Oct1

3

Mar14

Au

g1

4

Jan

15

Jun

15

Nov1

5

Ap

r1

6

Se

p1

6

Feb1

7

Jul1

7

Dec1

7

Cashless transactions (Volume in mn ) Trendline

72

Research Analysts

Vinod Karki vinodkarkiicicisecuritiescom +91 22 6637 7586

Siddharth Gupta siddharthguptaicicisecuritiescom +91 22 2277 7607

As the transient effects of demonetisation fade we analyse the latest trends in Indiarsquos move toward a cashless economy which incidentally was one of the stated objectives of demonetisation Key trends observed are

Cash levels in the economy did not decrease permanently After dipping significantly post demonetisation cash in circulation (CIC) at Rs1933tn is back to the trend growth seen in the pre-demonetisation period which has resulted in CIC as a percentage of GDP inch closer to the pre-demonetisation level of ~12

Value of cash withdrawals from ATMs has risen back to pre-demonetisation period at ~Rs25trn per monthhellip In a trend reversal the amount of cash withdrawn from bank accounts via ATMrsquos has been inching up and is now comparable to trends seen pre-demonetisation

hellipalthough number of cash withdrawals continues to be below trend implying higher cash withdrawals per transaction at ATMs As ATM transaction above a certain level (varies from bank to bank) are charged by banks the quantum of cash withdrawal per ATM transaction has increased

Despite rising CIC overall cashless transactions value (ex-RTGS) continues to grow at a faster pace than in pre demonetisation periodhellip Overall cashless transactions (ex-RTGS) hit Rs828trn in Q4FY18 a robust 23 growth on the high base of last year It indicates that the growth in electronic digital transactions is a permanent and irreversible trend

hellipdriven by NEFT IMPS UPI and cards at POS Rise in cashless transactions is driven by NEFT (Rs18trnmonth) IMPS (Rs1trnmonth) UPI (Rs230bnmonth) and card transactions (Rs810bnmonth) growing YoY by 37 82 976 and 13 respectively

RBIrsquos KYC norms puts brake on the exponential rise of M-Wallets transaction value M-Wallets transaction value grew exponentially from a pre- demonetisation base of Rs33bnmonth to Rs130bn in Febrsquo18 but RBIrsquos KYC (Know your Customer) norms post Febrsquo18 have resulted in reversal in the value of M-Wallet transactions which fell to Rs100bn in Marrsquo18

POS terminals continue to rise along with number of cards issued by banks while ATM growth plateaus Significant ramp-up by e-commerce players banks and retail players has resulted in 2590 POS per million persons up from 1250 from the pre-demonetisation period Credit cards outstanding grew a robust 26 for Q4FY18 and the number outstanding is 37mn at Marrsquo18-end On the other hand the number of ATMs per million persons has remained flat at 184 since demonetisation while Paper clearing is seeing a decline in transactions by value

Private sector banks have a distinct edge over their PSU counterparts in terms of electronic transactions but the reverse is true for ATM networks and cash transactions at ATMs To contextualise the impact of digital transactions the share of internet and mobile transactions initiated by customers moved up to 85 in FY18 from 3 in FY08 for HDFC Bank while during the same period the share of transactions handled by branches has fallen from 43 to 8 Overall private sector banks have an edge over PSU banks in electronic mode of transactions such as credit cards (Pvt bank share 82) and debit cards (43) usage at POS mobile banking (66) and NEFT outward (51) transactions On the other hand PSU banks have an edge in terms of cash transactions in the form of wider ATM networks (PSU share 71) and higher share of cash withdrawal from ATMs (73)

INDIA

Strategy May 29 2018 ICICI Securities

2

Cash levels in the economy did not decrease permanently

After dipping significantly post demonetisation cash in circulation (CIC) at Rs1933tn is

back to the trend growth seen in the pre-demonetisation period which has resulted in

CIC as a percentage of GDP inch closer to the pre-demonetisation level of ~12 as on

18-Mayrsquo18 (at 116)

Chart 1 Currency in circulation rose back sharply at Rs1933tn as

Source CEIC ISec Research

Chart 2 CIC at 116 of GDP ndash back in range

Note Trailing 12-month GDP has been used and for Aprrsquo18 and Mayrsquo18 advance estimates have been used Source CEIC ISec Research

0

5

10

15

20

25

Jan

-05

Jul-0

5

Jan

-06

Jul-0

6

Jan

-07

Jul-0

7

Jan

-08

Jul-0

8

Jan

-09

Jul-0

9

Jan

-10

Jul-1

0

Jan

-11

Jul-1

1

Jan

-12

Jul-1

2

Jan

-13

Jul-1

3

Jan

-14

Jul-1

4

Jan

-15

Jul-1

5

Jan

-16

Jul-1

6

Jan

-17

Jul-1

7

Jan

-18

(Rs tn

)

Currency in circulation Trend - CIC Trend - but with the 2016 shift

116

4

6

8

10

12

14

Jan

11

May 1

1

Se

p 1

1

Jan

12

Ma

y 1

2

Se

p 1

2

Jan

13

Ma

y 1

3

Se

p 1

3

Jan

14

Ma

y 1

4

Se

p 1

4

Jan

15

Ma

y 1

5

Se

p 1

5

Jan

16

Ma

y 1

6

Se

p 1

6

Jan

17

Ma

y 1

7

Se

p 1

7

Jan

18

Ma

y 1

8

CIC as a of GDP


3

Value of cash withdrawals back to pre-demon range although number of withdrawals remains low

In a trend reversal the amount of cash withdrawn from bank accounts via ATMrsquos have been inching up and is now comparable to trends seen pre-demonetisation at around

Rs25tn However number of cash withdrawals continues to be below trend implying

higher cash withdrawals per transaction at ATMs As ATM transactions above a certain

level (varies from bank to bank) are charged by banks the quantum of cash withdrawal

per ATM transaction has increased

Chart 3 Value of withdrawals has come back within trend


Chart 4 Number of withdrawals has reduced considerably


00

05

10

15

20

25

30

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Ju

l12

Oct1

2

Jan

13

Ap

r1

3

Ju

l13

Oct1

3

Jan

14

Ap

r1

4

Ju

l14

Oct1

4

Jan

15

Ap

r1

5

Ju

l15

Oct1

5

Jan

16

Ap

r1

6

Ju

l16

Oct1

6

Jan

17

Ap

r1

7

Ju

l17

Oct1

7

Jan

18

(Rs trn

)

Value Debit Card Usage at ATMs Trendline

0

100

200

300

400

500

600

700

800

900

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Jul1

2

Oct1

2

Jan

13

Ap

r1

3

Jul1

3

Oct1

3

Jan

14

Ap

r1

4

Jul1

4

Oct1

4

Jan

15

Ap

r1

5

Jul1

5

Oct1

5

Jan

16

Ap

r1

6

Jul1

6

Oct1

6

Jan

17

Ap

r1

7

Jul1

7

Oct1

7

Jan

18

Number of usages (mn) Trendline


4

Overall cashless transactions continue to growhellip

Despite rising CIC overall cashless transactions value (ex-RTGS) continues to grow at

a faster pace than in pre-demonetisation period Overall cashless transactions (ex-

RTGS) hit Rs828trn in Q4FY18 a robust 23 growth on the high base of last year It

indicates that the growth in electronic digital transactions is a permanent and

irreversible trend

Table 1 Strong growth registered across payment modes

Mode of Transaction

Volume (mn) Value (Rs bn)

Jan-Mar17 Jan-Mar18 Growth Jan-Mar17 Jan-Mar18 Growth

RTGS (customer transactions) 30 34 12 247071 290500 18

Paper Clearing 367 298 -19 22343 21308 -5

Retail electronic clearing 1208 1505 25 42252 58660 39

- NEFT 499 548 10 38527 52759 37

- IMPS 190 309 63 1538 2803 82

- NACH (National Automated Clearing House) 517 646 25 2154 3073 43

Cards at POS 2153 2434 13

- Credit Card at POS 315 372 18 948 1234 30

- Debit Card at POS 852 902 6 1205 1200 0

Pre-Paid Instruments (M-Wallets PPI Cards Vouchers) 918 1000 9 313 416 33

Cashless transactions (Ex-RTGS) 3660 4077 11 67062 82818 23

UPI 14 501 34x 60 589 89x

OS Credit cards - Number and balance os (avg) 29 37 26 504 666 32

Number of OS cards ndash Debit Card (avg) 770 854 11

Number of POS (lsquo000s) (avg) 2257 3093 37

Number of ATMs (lsquo000s) (avg) 221 222 0

Mobile Banking 315 676 114 4394 3649 -17

Debit Card ndash usage at ATM 2115 2235 6 5704 7689 35

Source CEIC I-Sec Research

To understand the demonetisation impact we compared the numbers with the

numbers extrapolated from the pre-demonetisation trend ndash and found that cashless

transactions were up 55 in value terms and 72 in volume terms from the numbers

suggested by the historic trend

Chart 5 Monthly Cashless transactions (in value terms) (Ex-RTGS)

Chart 6 Monthly Cashless transactions (in Volume terms) (Ex-RTGS)

Source CEIC I-Sec Research Source CEIC I-Sec Research

0

5

10

15

20

25

30

35

40

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

Ma

y1

3

Oct1

3

Ma

r14

Au

g1

4

Jan

15

Jun

15

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7

(Rs tn)

Cashless transactions (Value) Trendline

55

0

200

400

600

800

1000

1200

1400

1600

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

May1

3

Oct1

3

Ma

r14

Au

g1

4

Ja

n1

5

Ju

n1

5

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7


72


5

hellipdriven by NEFT IMPS UPI and cards at POS Rise in cashless transactions is driven by NEFT (Rs18trnmonth) IMPS

(Rs1trnmonth) UPI (Rs230bnmonth) and card transactions (Rs810bnmonth)

growing YoY by 37 82 976 and 13 respectively

Chart 7 NEFT continues on the growth path


Chart 8 IMPS continues its exponential growth

Source RBI I-Sec Research

Chart 9 UPI continues to grow at a rapid pace


0

50

100

150

200

250

0

5

10

15

20

25

Ap

r-11

Au

g-1

1

Dec-1

1

Ap

r-12

Au

g-1

2

Dec-1

2

Ap

r-13

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-15

Au

g-1

5

Dec-1

5

Ap

r-16

Au

g-1

6

Dec-1

6

Ap

r-17

Au

g-1

7

Dec-1

7

(mn)

(Rs tn)

NEFT Value NEFT Volume

0

20

40

60

80

100

120

0

200

400

600

800

1000

1200

Ap

r-1

1

Au

g-1

1

Dec-1

1

Ap

r-1

2

Au

g-1

2

Dec-1

2

Ap

r-1

3

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-1

5

Au

g-1

5

Dec-1

5

Ap

r-1

6

Au

g-1

6

Dec-1

6

Ap

r-1

7

Au

g-1

7

Dec-1

7

(mn)

(Rs b

n)

IMPS Value IMPS Volume

0

50

100

150

200

250

300

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Ja

n-1

7

Fe

b-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Ju

n-1

7

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Ja

n-1

8

Fe

b-1

8

Ma

r-18

Ap

r-18

Amount (Rs in bn) Volume (mn)


6

Chart 10 Continuous addition to the member banks on UPI


Chart 11 Total cards (value) at POS terminals spikeshellip

Chart 12 hellipdue to increase in debit cards usage

Source CEIC ISec Research Source CEIC ISec Research

The average value of a credit card transaction was within the range of Rs3000-3500

after briefly falling to Rs2683 in Decrsquo16 while the same for an average debit card

swipe remains in the range of Rs1300-1500 with a mild downtrend

Chart 13 Average transaction value remains in the normal range


0

20

40

60

80

100

120

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Feb-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

Ap

r-18

No of Banks live on UPI

0

100

200

300

400

500

600

700

800

900

1000

(Rs b

n)

Cards value at POS

0

100

200

300

400

500

600

700

(rs b

n)

Credit Card Usage at POS

Debit Card usage at POS

0

500

1000

1500

2000

2500

3000

3500

4000

Ap

r-16

May-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Ma

r-17

Ap

r-17

May-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

(Rs)

credit card at POS debit card at POS


7

RBIrsquos KYC norms puts brakes on the exponential rise of M-Wallets transaction value

M-Wallets transaction value grew exponentially from a pre- demonetisation base of

Rs33bnmonth to Rs130bn in Febrsquo18 but RBIrsquos KYC (Know your Customer) norms post Febrsquo18 have resulted in reversal in the value of M-Wallet transactions which fell to

Rs100bn in Marrsquo18

Chart 14 M-Wallets going out of favour due to KYC norms

Chart 15 M-Wallets - volume


Number of POS Cards continue growth ATMs plateau

Significant ramp-up by e-commerce players banks and retail players has resulted in

2590 POS per million persons up from 1250 from the pre-demonetisation period

Credit cards outstanding grew a robust 26 for Q4FY18 and the number outstanding

is 37mn at Marrsquo18-end On the other hand the number of ATMs per million persons

has remained flat at 184 since demonetisation while Paper clearing is seeing a decline

in transactions by value

Chart 16 POS terminals see a demonetisation-induced spike


0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8

POS per mn persons (LHS) ATMs per mn persons (RHS)


8

Chart 17 Number of cards continues to grow


Chart 18 While paper clearing volumes are stablehellip

Chart 19 hellipits clearly falling in value terms


20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)

Number of Outstanding Debit Card Number of Outstanding Credit Card (RHS)

0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)

Paper Clearing Volume

0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t

n) Paper Clearing Value


9

Private Banks have edge in electronic transactions but reverse true for ATM networks and cash withdrawals

To contextualise the impact of digital transactions the share of internet and mobile

transactions initiated by customers moved up to 85 in 2018 from 3 in 2008 for

HDFC Bank while during the same period the share of transactions handled by

branches has fallen from 43 to 8

Chart 20 Axis Bank Digital vs Physical

Source Company data I-Sec research

Chart 21 Axis ndash Bank branch size reduction

Note FY13 average indexed to 100 Source Company data I-Sec research

0

10

20

30

40

50

60

70

80

90

100

FY14 FY15 FY16 FY17 FY18

Digital ATM+Branch

100

5448

0

20

40

60

80

100

120

Till FY13 FY14+FY15 FY16+FY17

Axis Bank Branch area trends


10

Chart 22 HDFC Bank Shift to digital in a decade

of customer initiated transactions by channel 2008 vs 2018


Table 2 SBI Share of digital transactions up from 31 in FY17 to 37 in FY18

Channels share of transactions Mar-18 Mar-17

Digital Internet Banking 21 18 POS 13 9 Mobile Banking 3 3 Digital Total 37 31 Other Non-Branch ATMCDM 34 37 Banking Correspondents 9 7 Non-Branch Total 80 75 Branch 20 25 Total 100 100


Chart 23 Growth in personal loans led by Credit Cards and ldquoothersrdquo

Source CEIC I-Sec research

Branches 43

ATM 40

Phone Banking

14

Internet and Mobile 3

2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)

Increase in 1 year Rate of growth


11

Overall private sector banks have an edge over PSU banks in electronic mode of

transactions such as credit cards (Pvt bank share ndash including foreign banks 82) and

debit cards (43) usage at POS mobile banking (66) and NEFT outward (51)

transactions On the other hand PSU banks have an edge in terms of cash

transactions in the form of wider ATM networks (PSU share 71) and higher share of

cash withdrawal from ATMs (73)

Chart 24 Mobile Banking Private sector banks lead with a 63 share by value

Source CEIC RBI I-Sec research

Chart 25 Private sector banks have the largest POS network with 59 share


0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Volume - mobile transactions (mn)

Other PSU Banks SBI amp Associates Pvt bank

0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)

Value - mobile transactions (Rs bn)


0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12

Chart 26 Credit Cards Private Banks with 64 outstanding cards and 59 of transactions at POS (value terms) are clear leaders


0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)

Outstanding Credit Cards

Other PSU Banks SBI amp Associates Pvt bank Foreign Bank

0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)

Number of Usages at POS


0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)

Value of Usages at POS



13

Chart 27 Debit Cards PSU Banks lead in number of cards (PSU share 84) ATM transactions (73 by value) but lag in POS transactions (57 only)


0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

Outstanding Debit Cards


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS

Other PSU Banks a SBI amp Associates Pvt bank

0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)

Value of usage at POS



14


Chart 28 While PSU Banks have the largest ATM network they have been reducing the quantum since Aprrsquo17 (71 ATMs as at Marrsquo18)


0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

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Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of withdrawals at ATMs


0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

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Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)

Value of withdrawals at ATMs


0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15

Chart 29 NEFT Private Banks lead with a 37 share as in Aprrsquo18 (value)


0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

Number of NEFT outward transaction


0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)

Value of NEFT outward transaction


Page 2

SPARK STRATEGY

find SPARK RESEARCH on (SPAK ltgogt)

Uttar Pradesh ndash Breaking free from the shackles of the BIMARU tag

SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136

We travelled over 1000Kms across the length and breadth of Uttar Pradesh over a period of 7 days meeting various businesses each day to

gauge the pulse on hat s changing in the state We conclude that UP is breaking free from the shackles of infamous BIMARU tag and is

emerging as a major demand driver for many sectors such as Auto Consumer durables FMCG Retail and NBFCs We believe five epochal

changes in UP in recent years have put the state at a juncture where other developed states like Gujarat TN Maharashtra etc were a decade

ago These changes are 1) Change in law and order situation and the resultant peace dividend 2) Change in road infrastructure 3) Change in

availability of electricity supply 4) Youngest population among major states and 5) Per capita income crossing the $1000 mark an important

threshold which was crossed by other developed states Gujarat Maharashtra TN and Karnataka a decade ago These changes should result in

a disproportionate growth for UP heavy businesses over a medium term Most B2C companies are realigning their distribution to ride this

theme ahead From Spark coverage universe recent commentary from Hero Maruti MMFS V-Mart and Britannia are reinvigorating the same

Why Uttar Pradesh matters If UP were a separate country it would be the 5th most populous country in the world after China India USA and

Indonesia With 224mn population UP is comparable with Brazil (208mn) and in terms of GDP UP ($219bn) is comparable with Bangladesh

($221bn) With 27 y-o-y growth in motorcycle sales and 23 y-o-y growth in Passenger Vehicles (PVs) during in 9MFY18 UP has emerged the

fastest growing market for Auto companies Moreover UP s share in total motorcycle sales in India has jumped from 15 in FY17 to 17 in

9MFY18 and share of PVs has increased from 73 in FY17 to 84 in 3QFY18 Britannia has posted 152 y-o-y growth in biscuit sales in UP in

FY18 making it one of the fastest growing markets for the company

What is changing in UP There are five major changes which we think are pivotal in putting UP on higher growth trajectory

1 Law and order The state has launched a massive crackdown on criminals in the last 12 months As per UP Police 50 most wanted criminals

have died in various encounters in the last 12 months ~4881 criminals have been arrested and ~5500 criminals have applied for bail

cancellation We believe that the peace dividend can have palpable prospective impact on UP

2 Improving road infrastructure After our 1000Km+ road trip in UP we are convinced that UP today has the best road infrastructure in the

country Total state govt spends on roads amp bridges at Rs 708bn in the last four years (FY14-FY17) is 14x the combined spend in the previous ten

years (Rs 505bn)

3 Improvement in electricity supply Electricity availability in rural areas has seen three-fold jump from 5hrs of availability in 2012 to 18hrs of

availability in 2018 while it is up 2x in urban areas from 12hrs in 2012 to 22hrs in 2018 Despite electricity demand going up the power deficit has

fallen down to 2 in FY17 down from 22 in FY10

4 Demographic dividend UP has the youngest population among major states with median age of 20 years which is quite low as compared to

the matured states like Kerala (31 years) Tamil Nadu (29 years) Andhra (27 years) and Karnataka (26 years) Notably adult population (age 10-19

years) comprises of ~25 of total population of Uttar Pradesh which is the highest among major States

5 Increase in per capita income At $1000 per capita income UP has reached an important threshold where Gujarat Maharashtra TN and

Karnataka were a decade ago Further in a state where 23 of the GDP is constituted by agriculture Govt focus on doubling far ers income

would lead to improvement in rural cash flows We expect UP s per capita income to grow at a CAGR of 112 from $1006 in FY19 to $1900 by

FY25E resulting in disproportionate growth for durable goods clothing amp footwear entertainment medical products amp services categories

GAUTAM SINGH

gautamsparkcapitalin

+91 22 6176 6804

VIJAYARAGHAVAN SWAMINATHAN

raghavansparkcapitalin

+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3

Ears on the Ground ndash Takeaways from our on road trip in UP

Cash flows in rural UP has improved in last few months led by pick up in non-farm activities and higher realization for

potato and sugarcane farmers Potato price are up ~100 in last two months

1 Improvement in cash

flow situation in rural UP

There is a clear pickup in tractor demand mainly from agriculture construction and haulage segment Labour shortage

and need for replacement for old trucks aided by easy availability of finance are some of the major factors that are

driving tractor sales

2 Sharp pick-up in

demand for Tractors

Hero is the market leader in lt125cc bike category however in the higher cc segment craze for Enfield is on the rise

Improving affordability is one of the key reasons driving the sales of premium segment bikes

3 Two Wheelers

demand on the rise

There was a massive demand for HCVs in UP mainly led by Infra spend until Ma 18 However Govt in Ap 18 had

relaxed the overloading limit in UP leading to demand shifting towards lower tonnage trucks 4 MHCV sales

GST had its impact on the business while it is on a recovery mode now The frenzy for Patanjali products has come

down in non-medicine products now V-Mart has been doing very well in this region 5 FMCG and retail

Inverter ACs are gaining huge acceptance due to power saving feature as it saves upto 50 electricity Frequent

fluctuations in electricity makes stabilizer a must in this region 6 Consumer Durables

With Ultratech coming into this market there has been major thrust on full capacity utilization Cement demand is

good but prices have remained very weak this year Sand prices have now fallen 15-20 due to availability of mines

7 Cement demand has

picked up but price

remains the key concern

Despite so much infra development real estate prices are still muted Potential buyers want to wait for further

correction in prices

8 Muted demand for

building materials real

estate remains very week

Page 4

A) Why Uttar Pradesh matters

1 If Uttar Pradesh were a country it would be comparable with Brazil in population and with Bangladesh in GDP

Parameters Uttar Pradesh All States

GDP size ($bn) 219 2577

Share in Indias GDP () 9 100

Per capita GDP ($) 1006 1975

Total population (mn) 224 1282

Population density (personssq km) 829 382

Sex ratio (females per 1000 males) 912 940

Literacy rate () 677 730

Installed power capacity (MW) 24434 334161

National highway length (km) 9017 122432

FDI equity inflows ($ mn) 652 367900

PPP projects (No) 537 9068

SEZ (No) 12 222

Capital Lucknow -

No of districts 71 662

1 If UP were a separate country it would be the 5th most populous country 2 Every country in Africa Europe and South America has fewer people than UP

Source World Bank Spark Capital Research Source World Bank Spark Capital Research

3 In terms of GDP UP is comparable with Bangladesh

Source World Bank Spark Capital Research

4 Key Statistics UP vs all states

Source GoI Economic Survey Spark Capital Research

2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)

Countries less populous than UP

USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States

Indonesia UP Brazil Pakistan Nigeria

Population (mn)

In terms of population

UP is marginally bigger

than Brazil

Page 5

UP has emerged as the fastest growing market for two wheelers whereas rich

states TN Karnataka and Maharashtra are witnessing fatigue in demand

Source SIAM Spark Capital Research

UP s sha e i total Moto le sales i I dia has also ju ped f o i FY to 17 during 9MFY18


For passenger vehicles also UP has seen the highest growth during 9MFY18


Britannia has posted 152 yoy growth in biscuit sales in UP in FY18 making it one

of the fastest growing markets for the company

Source Company presentation Spark Capital Research


27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN

Motorcycle sales during 9MFY18 ( yoy)

23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a

Passenger vehicle sales during 9MFY18 ( yoy)

13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18

FY11 FY12 FY13 FY14 H1FY15 FY16 FY17 9MY18

Share in total Motorcycle sales in India ()

UP Maharashtra Karnataka TN

2 UP is emerging as a major demand driver for many sectors like Auto FMCG Retail etc indicating a palpable surge in consumer demand in UP

94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat

Britannias sales growth ( yoy)

FY16 FY17 FY18

Page 6

1 UP govt has opted for a massive crackdown on criminals in the last 12-months

Source Dainik Jagran Spark Capital Research

2 Around 5000 criminals have been arrested and 5500 have applied for bail

cancelation in last one year

Source Media reports Spark Capital Research

3 Local people told us that there has been a significant change in intensity of

vigilance in most of the places in the last few months


4 Mobile police patrolling (100 number) has been the most effective in

controlling crimes

Source Spark Capital Research

B) What is changing in Uttar Pradesh

1 Law and order UP which is notorious for its poor Law amp Order situation has launched a assi e a kdo o i i alshellip

Withi te i utes of call we aim to

reach the doorstep

of the caller in

trou le

Stri t i stru tio s are there from the

top to control not

only crime but to

strop any form of

extortion eve

teasi g et

50 wanted criminals are dead

4881 criminals arrested

5500 criminals applied for bail

cancelation

A big rise in surrendering

50 most wanted criminals have died in various

encounters in last 12 months

4881 criminals have been arrested from the state

Around 5500 criminals have applied for bail cancellation

in last 12 months as they fear police encounter outside

jail

A large number of criminals are either surrendering or

have fled to neighbouring states

The police has launched Ope atio

Clea in Uttar Pradesh to deal with the wanted criminals

Page 7

1 Winds of change We noted a toll plaza on inner ring road Agra that is now fully

operated by only women employees ndash a completely unthinkable deed in old UP


2 Winds of change Jaswant Prajapati a food vendor in Lucknow o does t have to pay Rs 600 weekly bribe to cops a saving of Rs 2400 per month


3 Sri Lankan economy witnessed a sharp rebound post the decisive end of the

civil war in May 2009

Source IMF Spark Capital Research

4 Night traffic and economic activities have increased - Takeaways from our

interaction with Sateesh Kumar a taxi driver in UP



hellipthe pea e di ide d o its e o o a e e u de stood f o S i La ka s Pea e Di ide d

Jaswant Prajapati who is a food vendor in Lucknow

He earns ~Rs 1200 per day and saves half of it Overall activities have picked up as many new offices five star hotels etc have opened up re e tl

i Never took any travel booking involving night travel in UP until recently

because of fear of car being stolen or loot on the way

ii Rise in night traffic in UP in last 6 months because the UP 100 mobile police

patrolling has been very active at night

iii Every 10 Km he sees a police patrol car UP 100 which has brought down

criminal activities

iv He has started taking overnight bookings in UP His cashflow has improved

by 20 in last few months

v Have bought one more car on finance and put it in Orix

35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Real GDP growth () Sri Lanka

The Peace Dividend example from Sri Lanka

Page 8

2 A sea change in road infra UP now has the best road infrastructure in the country


1 Total state Govt spend on roads amp bridges at Rs 708bn in the last four years

(FY14-FY17) is 14x the combined spend in the previous ten years

Source RBI Spark Capital Research

UP s oads ha e see the iggest t a sfo atio i the ou t i the last three years both in urban and rural areas



3 MHCV sales in UP have seen massive jump during 9MFY18 4 Takeaways from our interaction with leading CV financer in UP


16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250

FY05 FY06 FY07 FY08 FY09 FY10 FY11 FY12 FY13 FY14 FY15 FY16 FY17

UP Govt spend on road amp bridges (RS bn)

Spend on roads amp bridges in FY14-FY17= Rs 708bn

Spend on roads amp bridges in FY04-FY13 = Rs 505bn

Total spend in last 4 yrs = 14x the combined spend in

the previous ten years

85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t

MHCV sales during 9MFY18 ( yoy) i There as a sharp ju p i de a d for MHCVs i UP duri g Apr -Mar

mainly led by infra spend by Govt

ii Strict laws against overloading and high infra demand led to the pick up in

demand for CVs Govt relaxed the overloading limit in UP leading to demand

tapering off for higher tonnage CVs and down trading to lower tonnage

iii Tata Motors Ashok Leyland Bharat Benz and Eicher motors (in this order) are

the leading players in MHCV market with Tata Motors being the leader with

50+ market share Tata Motors has lost market share in this region

iv Ashok Leyland has been very aggressive in this market during last year and it

has gained market share from 24 a year ago to 37 now

Agra-Lucknow expressway is the

longest expressway in India

Even rural areas now are well connected

with nearby cities through good roads

Page 9

3 Electricity availability in rural areas has seen three-fold jump while it is up 2x in urban areas vs 2012


1 Sharp improvement in availability of electricity in last 2 years


2 Energy deficit has tapered down to 2 in FY17 down from 22 in FY10

Source GoI Spark Capital Research

76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120

FY10 FY11 FY12 FY13 FY14 FY15 FY16 FY17

Energy Required (BU) Energy availability (BU) Energy Deficit ()

3 State Go t ai s to p o ide po e suppl Ma Huge sa i gs fo industries and small establishments


What people said on power supply and electricity tariff hikes


i Most cities have been receiving ~22 hours

a day power supply

ii Demand for inverter and battery has

taken a massive hit because of enhanced

electricity supply

iii Electricity tariffs have been increased

around 3x for un-metered connections

for non-agriculture use

iv Rural people were complaining about

the surge in electricity price

5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018

Number of hours availability of electricity in UP

Rural areas Urban areas

1 Enhanced power supply UP which used to have prolonged power

outages has seen a remarkable improvement in last couple of years This

should help saving for industrialists and households spending on power

gensets inverters batteries etc

2 Crackdown on power thefts Vigilance teams have been added frequent

raids on power thieves replacing traditional meters with smart meters are

the key measures the State Govt has taken to stop power thefts

3 Bodes well for demand for meters transformers cables and durable

goods Negative for genset inverter and battery industries

0


4 Demographic dividend UP has the youngest population among major states with median age of 20 years

Inter-state median age comparison of India

Source Census 2011

A

1) Median age of Uttar Pradesh is the lowest in India at 20 which is

quite low as compared to the matured states like Kerala (31 years)

Goa (30 years) Tamil Nadu (29 years) Andhra (27 years) and

Karnataka (26 years)

2) Proportion of population with age group (10-19 years) at ~25~ is

the highest in India among major states

3) UP has the lowest share of elderly population (60 years or more)

(77) among major states

4) UP is set to reap the benefits of its young population ahead

Age group between 10-19 years account for ~25 of total population of

Uttar Pradesh which is the highest among major States

Source Census 2011 A

Name of the State Adolescent Name of the State Adolescent

Top 5 Bottom 5

UTTAR PRADESH 245 KERALA 163

RAJASTHAN 229 TAMIL NADU 172

UTTARAKHAND 225 KARNATAKA 189

BIHAR 225 MAHARASHTRA 19

JHARKHAND 222 ANDHRA PRADESH 193

Page 11

UP has crossed the $1000 per capita income mark this year which is very important

for discretionary consumption India crossed the $1000 mark a decade ago in FY08

Source GoI RBI Spark Capital Research

The richer states - Gujarat and Maharashtra crossed the $1000 per capita mark in

FY06 Tamil Nadu did it in FY07 and Karnataka crossed this mark in FY08


Agriculture accounts for 23 of the state GDP Centre Govt focus on doubling

fa e s i o e ould ha e a di e t i pa t o the state s u al e o o


Rural cash flow has improved ndash takeaways from interactions with farmers in UP



5 At $1000 per capita income UP has reached an important threshold where Gujarat Maharashtra TN and Karnataka were a decade agohellip

1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)

In terms of per capita GDP UP is

following India with a decade lag

1049

500

1000

1500

2000

2500

3000

3500

FY05 FY06 FY07 FY08 FY09 FY10 FY11 FY12 FY13 FY14 FY15 FY16 FY17 FY18

Gujarat Karnataka Maharashtra Tamil Nadu

Uttar Pradesh is where Gujarat

Maharashtra TN and

Karnataka were a decade ago

Agri 23

Industry 26

Services 51

i Cash flow in rural area has increased in recent months in sugarcanepotato

belts

ii Pick up in non-farm activities in rural areas have also resulted in better cash

flow for rural people Wage rate has been on the rise

iii This season potato prices are higher (up around 100 in last one month) due

to lo er produ tio This ear far ers realizatio has go e up

iv Farmers are complaining about highly volatile prices of agri commodities

They want assured prices so that they can be sure of future income

v Sugarcane output has been higher this year due to ~20 higher output

leading to fall in sugar prices

Page 12


hellipfu the ise i UP s pe apita i o e to $ FY E ould ea ig de a d delta fo du a le goods lothi g amp foot ea entertainment amp

medical and HH products amp services categories

As per- apita i o e g o s p opo tio of food i o e all HH spe d o es do hellip

Source NSSO Spark Capital Research

hellipa d p opo tio of o -food categories like durables goods clothing amp footwear

and other HH products amp services goes up


We estimate rise in per capita income in UP from current $1000 to $1900 by

hellip

Source CSO Spark Capital Research

hellip hi h should esult i ig de a d delta fo du a le goods lothi g amp foot ea Education entertainment amp medical and HH products amp services


585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12

Share in HH expenditure in India ()

Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12

Key category-wise share in HH expenditure in India () Food

Fuel amp light

Tobacco amp intoxicants

HH products amp services

Clothing amp footwear

Durable goods

Education entertainment amp

medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E

Key category-wise share in HH expenditure in UP () Food

Fuel amp light




Durable goods

Education entertainment amp medical

325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5

Per capita GDP of Uttar Pradesh ($) Estimate

Page 13


Earlier (until FY15) Now

Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral

Uttar Pradesh Then amp Now

Page 14

C) Ears on the Ground ndash Takea a s f o ou oad t ip i UP i Ap

The Spark strategy team traversed more than 1000 kms across the length and breadth

of the Uttar Pradesh over a period of 7 days doing varied channel checks each day to

judge the general demand scenario

Spark Ears on the Ground Juggernaut

1000 kms + 200 plus channel checks in urban and rural pockets of Uttar Pradesh

Our channel checks included

bull Apparels shops

bull Auto amp Auto ancs dealers

bull Bank amp NBFC branches

bull Bureaucrats Media generalists

bull Cement dealers tiles amp building materials

bull Construction sites

bull Consumer durable outlets

bull Four wheeler dealers

bull Farmers labourers

bull Pharmacy

bull Real estate developers agents etc

bull Regional sales-head wholesalers

bull Toll plazas luxury stores

bull Truck operators

bull Two wheeler dealers

Visited more than 50 major urban and rural pockets of Uttar Pradesh with

an objective to understand the current demand scenario and to identify

emerging trends

500+ touch points across key urban and rural pockets of UP were covered

Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30

Fiscal deficit and debt management

Appendix UP Budget FY19 Market borrowings to jump 224 yoy to Rs 671bn in FY19BE

1 Fiscal deficit has been budgeted to remain largely unchanged at 296 of GDP

in FY9BE within the FRBM limit

Source UP Budget Spark Capital Research

2 Market borrowings has been budgeted to increase by 224 in FY19



3 Interest servicing as a of expenditure has been budgeted to fall to 76 of

total expenditure in FY19BE

4 Govt aims to gradually reduce outstanding debt which stood at 298 of GDP

in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800

FY16 FY17 FY18BE FY18RE FY19BE

Market borrowings (Rs bn) Market borrowings ( of GDP)

300 299

295

298

291

286

288

290

292

294

296

298

300

302


Outstanding debt ( of GDP)

53

450

295 298 296

00

10

20

30

40

50

60


Fiscal Deficit ( of GDP)

93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10


Interest Servicing ( total expenditure)

Page 31

Appendix UP Budget FY19 Key takeaways

Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation

Fiscal deficit has been budgeted to remain

largely unchanged at 296 of GDP in FY9BE

within the FRBM limit

The total expenditure in FY19 is

targeted at Rs 43tn This is

163 higher than FY18RE

Market borrowings has been

budgeted to increase by 224

to Rs 671bn in FY19BE

UP witnessed a 15 fall in tax

revenue collections during

FY18 over the budget

estimates

Collections from stamp duty were

28 lower than the budget

estimates

UP is expected to spend Rs 116bn on subsidies

in FY19BE which is 15 higher than FY18BE

Spending in irrigation has increased 316 in

FY19BE over FY18RE to Rs 142bn

Rs 165bn has been allocated for

the Smart Cities Mission

Capex is budgeted to increase

by 305 in FY19 while revex is

budgeted to increase at a

moderate pace of 122

Out of Rs 197bn allocated for rural

development Rs 29bn will be spent

on roads and bridges and Rs 12bn

will be spent on housing

The nominal GDP of UP for FY19 has been

estimated to grow only at 8 yoy to Rs149tn

The state is estimated to spend Rs

455bn on pensions a 22 increase

over FY18

Page 32

Sectoral Spending ndash Major heads

Appendix Energy irrigation and rural development grab the maximum delta in spending in FY19BE

Department-wise expenditure


Key Highlights

bull The allocations for agriculture sector has

fallen 59 yoy in FY19BE because the

state had implemented a farm loan waiver

in FY18 resulting in higher spending

during the year

bull Out of the Rs 197bn allocated to Rural

development Rs 29bn will be spent on

roads and bridges and Rs 12bn will be

spent on rural housing

bull While allocation for energy sector has

seen 537 yoy jump 62 of this

allocation is for revenue expenses (such as

payment of interests and subsidy) and

only 38 is on capital expenses

bull Rs 165bn has been allocated for the

Smart Cities Mission Cities selected under

the Mission are Lucknow Kanpur Agra

Varanasi Allahabad Aligarh Jhansi

Moradabad Bareli and Saharanpur

bull Allocation for various road projects

Gorakhpur Link Expressway Rs 55bn

Purvanchal Expressway Rs 10bn Agra-

Lucknow Expressway Rs 5bn

Expenditure (Rs bn) Growth (yoy)

FY16 FY17 FY18BE FY18RE FY19BE FY18BE FY18RE FY19BE

Agriculture 29 60 396 284 116 5547 3695 -592

Rural development 101 104 158 159 197 516 528 237

Irrigation and Flood Control 103 107 110 109 143 26 16 316

Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138

Urban Development 52 62 134 131 135 1146 1107 26

Debt Repayment 176 203 220 220 305 84 84 388

Interest payment 284 269 332 303 324 233 124 71

Others 1406 217 225 225 278 36 37 236

Total Expenditure 3039 3334 3847 3685 4284 154 105 163

1 Edelweiss Securities Limited

Eleven months post GST implementation we revisit our long-term thesis

of formalisation of the Indian economy (refer THE SHIFT Unorganised to

organised) An integrated tax structure and anti-evasion measures under

GST (e-way bill reverse charge mechanism (RCM) bilateral validation of

invoices among critical ones) are core to our thesis of demand shift from

unorganised to organised players for certain sectors While timelines for

implementation of RCM and bilateral invoice validation are unclear inter-

state e-way bill was implemented from April 1 2018 (intra-state from

June 01 2018) Our on-ground interactions with trade

(dealerdistributors) industry bodies and experts highlight 1) in the

immediate period post GST rollout unorganised trade ruled the roost due

to lack of anti-evasion measures 2) e-way bill has been widely accepted

across informal trade despite below-par surveillance and 3) organised

players have regained some lost ground though acceleration in shift of

demand to organised players hinges on strict surveillance and rollout of

all anti-evasion measures While jewellery battery and plastic products

sectors have seen demand shift post GST the organised building material

(tiles plywood) sector has faced challenges from informal trade

GST collections Tough ask anti-evasion measures critical

Aggregate FY18 GST collection stood at ~72tn (monthly ~INR900bn) While collections

were strong in the first three months they tapered off post October 2017 before

touching an all-time high monthly collection of INR1035bn (19 higher than monthly

run rate till March 2018) in April 2018 The government has set an aggressive GST

collection target for FY19 implying a monthly run rate of INR1165bn (30 higher than

FY18) We believe it will be a tough task ahead in terms of GST collectionsrsquo trajectory

and will hinge on strict implementation of anti-evasion measures and surveillance

Unorganised trade losing ground post e-way bill though early days

Our interactions with dealers distributors industry bodies transporters and

unorganised manufacturers indicate that unorganised trade activity has reduced post e-

way bill implementation A few indicated there is a visible change in attitude of trade

channels towards compliance as incentives to trade via informal channels have

reduced considerably Some believe the e-way bill will lead to improved compliance

though strict suvelliance by the government has yet to kick in

Multiple challenges lurk around surveillance

Despite smooth roll out of e-way bill there are multiple challenges that lurk in terms of

a) liberal validity of e-way bills leading to instances of multiple use of the same e-way

bill b) on-ground checks inspection by officials yet to pick up c) lack of fear amongst

trade channel regarding non-compliance and d) under-invoicing which remains a

widely prevalent modality to evade taxes amongst informal trade though its magnitude

has reduced since GST implementation

Manoj Bahety

+91 22 6623 3362

manojbahetyedelweissfincom

Nilesh Aiya

+91 22 4040 7575

nileshaiyaedelweissfincom

Ankit Dangayach

+91 22 6620 3077

ankitdangayachedelweissfincom

Raj Koradia

+91 22 6623 3422

rajkoradiaedelweissfincom

June 4 2018

THE SHIFT

ANALYSIS BEYOND CONSENSUS

EDEL PULSE

THE SHIFT 11 months of GST ndash Strict surveillance critical


Analysis Beyond Consensus

Roll out of e-way bill smooth this far with no technical glitches

State-wise phased implementation had led to smooth roll-out of e-way bill with no major

systems related issues observed in the initial months e-way bill has gained wide acceptance

across different industries and geographies However intensity of surveillance of e-way bills

differs from state to state Some challenges faced by tax payers include part truck load and

related compliance issues confusion in case of transhipment goods moved in multiple

trucks and inability of transporters to comply with norms among others

GST collections tapered down after initial pick-up

Chart 1 May GST Collections promising ndash however ask rate is higher

Source Ministry of Finance Edelweiss research

Aggregate GST collection for FY18 (8 months - August17-March18) stood at ~INR72tn

implying average monthly collection of ~INR897bn While collection was strong in the first

three months it tapered off post Octoberrsquo17 before touching an all-time high monthly

collection of INR1035bn (19 higher than Novrsquo17-Marrsquo18 average collections) in Aprilrsquo18

The government has stated that the spurt in April GST collection may have been a year-end

phenomenon and its sustainability in subsequent months needs to be monitored

Collections data released for the month of May stood at ~INR940bn which is promising

though the asking rate is higher and it will be challenging for the Government to meet the

collection target

We believe the fall in GST collections during November 2017-March 2018 was primarily led

by

1 Significant destocking of inventory across the distribution chain in the period leading to

GST implementation Post GST rollout restocking took place at a brisk pace leading to

high collections in Aug-Octrsquo18

2 Reduction in tax rates from 28 to 18 on 178 items with effect from November 15

2017

3 Deferment of implementation of anti-evasion measures like e-way bill bilateral

validation of invoices and RCM

936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)

Monthly GST Collection

897987

1201

0

300

600

900

1200

1500

Avg (2017-18) Avg (April-

May18)

FY19 avg

monthly asking

rate

(IN

R b

n)

GST Collection - Asking rate


The SHIFT

Chart 2 Compliance under composition scheme picking up ndash Primarily includes the small tax payers


GST collections target for FY19 a tough ask

The governmentrsquos FY19 budgeted GST collection implies average monthly collection of

INR1165bn (up ~30 over FY18 monthly collection) After considering April-May aggregate

GST collections of ~INR2tn the ask rate for FY19 has gone up to ~INR12tn per month The

government is hopeful of gradual recovery in GST collections led by pick up of economic

activity and implementation of anti-evasion measures like e-way bill which was

implemented from April 1 2018 on inter-state transactions Further intra-state e-way bill

also implemented from June 01 2018 across India We believe there are strong levers with

the government to curb tax evasion which will lead to higher compliance increased tax

collection over long term and formalisation will benefit sectors with huge unorganised

presence

810

925

1147

0

250

500

750

1000

1250

June-Sept 17 Oct-Dec 17 Jan-March 18

(0

00

s)

Quarterly returns filed

34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground

Table 1 E-way Bill Key highlights from our channel check

Source Edelweiss research

Roll out and implementation Smooth roll out has happened and no major system related issues glitches faced by trade

Phased inter-state implementation and intra-state roll out helped ease the pressure on

system servers

Implementation was planned better this time around

Anecdotal evidence suggests that transporters are reluctant to transport goods in the

absence of an e-way Bill Freight rates for movement of goods without proper documents

(including e-way Bil l) have gone up considerably

Surveillance and checks On-ground checking inspection by officials has yet to pick up substantially currently it is

happening in a calibrated and gradual way to curb unauthorised movement of inter-state

goods Some believe that tight surveil lance could improve tax collection and reduce unorganised

unauthorised trade going ahead RFID (refer Annexure 2) based checking could improve the governmentrsquos abil ity to monitor

inspect higher number of vehicles versus physical verification by officials

Challenges Difficulty in preparing shipments in advance due to validity of e-way bil ls In case of part

truck load shipment inabil ity to ensure full compliance as transported deals with further

movement of goods Involvement of multiple vehicles trans-shipment cases involve recording details of each

vehicle which is difficult for the suppliers to maintain There are no controls on how

transporters are complying on behalf of tax payers

An e-way bil l cannot be edited Hence in case of errors have to be cancelled and a new one

needs to be generated

Huge working capital issues are being faced by the SMEs due to stuck GST refunds increased

compliance cost and working capital financing issues

Unorganised trade situation Unorganised players gained ground in the post GST and pre e-way Bil l period due to lack of

anti-evasion measures However visible difference has been observed post e-way Bil l

implementation Currently therersquos no fear amongst the trade community and a casual approach is being

adopted in terms of full compliance

Under-invoicing a prevalent practise continues unabated even after e-way bil l

implementation Tax evasion tactics like under-invoicing will be difficult for the government

to track Cash availabil ity in the system has increased as lucrative working capital terms offered to

deal in cash (fast receivable collection) is incentivising cash dealings However since the implementation of e-way Bil l freight rates have increased for those who

dispatch goods without proper documentation signall ing visible additional cost burden to

transact in cash


The SHIFT

Glimpse of surveillance measures and levers to increase compliance

Fig 1 Recent surveillance measures

Source Media articles Edelweiss research

Government has set up a dedicated GST Intelligence unit

Directorate General of GST Intelligence (DGSTI) is tasked with ensuring tax compliance and

going further it is expected to step up surveillance by studying the price structure

marketing patterns and classification of commodities and advise the GST authorities in

plugging loopholes and ensure compliance

About DGSTI

The government has set up a new unit mdash Directorate General of GST Intelligence (DGSTI)

which is empowered to keep an eye on tax compliance as part of its plans to crackdown on

evaders and invoke anti-profiteering measures There will be at least one unit of DGSTI in

each state which will replace the existing Directorate General of Central Excise Intelligence

(DGCEI)

DGSTI will be mandated to collect and disseminate intelligence relating to GST evasion It

will study the price structure marketing patterns and classification of commodities and

advise the GST authorities in plugging loopholes It will also function as think-tank to Central

Board of Indirect Taxes amp Customs (CBIC) The body will examine cases of suspected tax

evasion and pass on its inputs to CBIC DGSTI will also study the modus-operandi of evasion

and issuance of alert notices and co-ordinate and share information about tax evasion with

other enforcement agencies

Intelligence Unit unearths fake bills worth INR 25 bn claiming fake ITC of INR 45bn

CGST- Mumbai arrests 2 people for claiming fake ITC worth INR 723 mn

Intelligence team-Mumbai arrests 2 people for claiming fake ITC of INR 12 bn

Department is sending notices through automated mails to non-filers through emails asking them to submit returns within three days of the expiry of the deadline

GST officers sending scrutiny notices to companies whose tax payment did not match the GSTR-1 (Sales Return) and whose GSTR-1 did not match GSTR-2A (Purchase return)

As per analysis in March 34 per cent of businesses paid INR 344 bn less tax between July-December

Department initiated the

mobile checking of

vehicles transporting

goods in Madhya Pradesh

and so far about 100

vehicles have been

detained for violating e-

way bill norms



Fig 2 Anti-evasion measures and potential levers to up the compliance going ahead


GSTN has invited bids from private entities for 360-degree profiling of taxpayers for early detection of fraud as it seeks to transform into an end-to-end platform for checking GST evasion from being just a tax collection portal

QR code on the e-way Bill would help easier and faster verification by tax officers

Installation of RFIDs by notified transporters and RFID readers at key locations would aid in tracking the movement goods without stopping the vehicle on the road

RCM is expected to be implemented soon wherein recipient of the goods andor services is liable to pay GST instead of the supplier

This will encourage trade with registered dealers and help in improving tax compliance

Invoice matching would done by way of auto-population of data filed in GSTR 1 of the supplier into GSTR 2 of the buyer and input tax credit on purchase of goods would only be available on matching of details in GSTR 1 and GSTR 2

Invoice matching

Reverse charge

mechanism (RCM)

AnalyticsQR code amp

RFID


The collapse in data prices hurts the telecom industry but is transformative for the economy

adding 5 to GDP Neelkanth Mishra

As a proportion of per capita income data on Indian mobile networks has gone from being

the most expensive globally two years ago to being the cheapest having fallen 95 per

cent Such steep price declines affect habits and behaviour We at Credit Suisse embarked on a

study to understand the economic implications of this change

Understandably during this period there has been a dramatic surge in data consumption with

per capita monthly usage rising eight-fold to nearly six and a half gigabytes Indian mobile

networks now claim that they carry more data than several global telecommunication companies

combined While some pride is justifiable for these firms per capita data usage in India is still a

small fraction of what it is in developed markets and may remain so for the foreseeable future

This is because most data consumption globally is through fixed line networks where India has

made very little progress In many countries per capita mobile data consumption is less than half

of Indiarsquos but total data consumed is fifteen times as much

Instead the exciting change is in the number of people who can now use mobile

broadband without worrying about how much data they are consuming We estimate that by

2020 there will be 550 million Indians with datavideo-capable phones from just 200 million at the

end of 2016 Each such user is a consumer as well as a worker mdash let us look at both the facets

Five years ago we wrote about the ldquoSilent Transformationrdquo of India on how the spread of rural

roads electricity and phones was driving never-before-seen changes to productivity During a

discussion on this report with the board of a large consumer goods company the CEO asked

ldquoExciting changes but how do we build our brands with the families benefiting from these

changes They donrsquot watch TVrdquo

That is indeed a significant constraint Indiarsquos TV penetration has improved significantly in the

last decade or so but a third of the households still do not have access For the ones that

do 95 per cent have only one TV (as against the US average of three screens per household)

and minutes of TV viewing per capita in India are among the lowest in the world

Cheap video-capable phones help If each user watches one to two hours of video on the phone

it adds 550 million to 11 billion screen hours per day to the 1 billion screen hours of capacity

currently available through televisions We estimate that the share of rural consumption that

can be targeted by video advertising may jump from just 27 per cent to over 95 per cent

Not only does the reach widen but smaller advertisers can reach more niche audiences too One

can run an advertising campaign targeting only a few thousand users now instead of relying on

mass media advertising that has very large ticket-sizes for advertising spots The cost of

advertising should fall as well mdash the surge in volumes on some of the internet platforms has

brought down the cost per impression by three-fourths in the last two years Thus branding

reach broadens sharpens and also becomes cheaper

A far more significant impact is likely to come from the share of Indiarsquos workforce that is connected rising from 33 per cent in 2016 to 96 per cent in 2020 Of the myriad ways in

which this helps productivity let us discuss three

The first is a significant improvement in worker utilisation While friction in job markets

(inefficiencies in matching a job opening to a worker) is a universal challenge in India the

problem is amplified by tens of millions of workers doing multiple jobs every year Workforce size

and the unemployment rate depend on the question asked Whether there was work in the

previous six months (unemployment ratio 22 per cent 474 million workers) or if there was work

in the previous week (56 per cent 416 million) Social media on which Indians collectively

spent 71 billion hours last year may be a drag on productivity for some (including this

author) but can significantly increase the number of days worked in a year for many by

expanding the network of trust The Nobel laureate Daniel Kahneman writes of a study that

showed how repetitive exposure builds trust Social media plays this role improving the

functioning of informal employment networks

The second is on supply chain efficiencies Indiarsquos inventory-to-GDP ratio is the highest in

the world That is to generate the same amount of income there is a lot more of capital stuck in

idle inventories than is necessary The fragmented nature of Indiarsquos retail chain and the surfeit of

small manufacturers compound the problems of an inefficient transportation infrastructure

Connected supply chains can improve planning and can release capital that can be

reinvested for growth Further in sectors like packaged food that have short shelf-lives data

connectivity is critical for business feasibility The reason every locality in India has a bakery

but there are no national chains is that in fast expiring products like cream rolls the supply chain

information could only travel efficiently in a radius of a few kilometres

The third and the largest impact would be through services networks that bring down fixed

costs by improving utilisation If a car costing Rs 700000 runs 50000 kilometres in say 7

years (at 20 kilometres a day) just the capital cost is fourteen rupees a

kilometre However if a taxi driver in a second hand car purchased for Rs 300000 drives

150000 kilometres the capital cost falls to two rupees a kilometre improving

affordability If taxi drivers and users are connected this helps create jobs and also

provides more affordable transportation This same mechanism applies to hotels as well

as skilled professionals such as beauticians electricians and plumbers among others

These are early days and human ingenuity and Indian entrepreneurism can significantly amplify

the positive impact But we estimate just these three mechanisms can add nearly 5 per cent to

GDP If these play out over three years that means 15 per cent a year addition to GDP growth

12 per cent a year if over four years The government and the private sector have invested

nearly 2 per cent of GDP in telecom infrastructure in the last four years Even if the decline

in data prices has been painful for the telecom industry the benefits to the economy seem

significant

The writer is India Equity Strategist for Credit Suisse

642018 The value of lsquoovervaluedrsquo stocks | Outlook Business

httpswwwoutlookbusinesscomperspectivethe-value-of-overvalued-stocks-4408 113

Story of the dayUnlike In The Past Where EMs Magnified US Market Swings They Face Less Downside Risk Now

Illustration Kishore Das

Perspective

The Value Of

lsquoOvervaluedrsquo Stocks

What should be your reactionto the success of investors who

buy and hold seeminglyovervalued stocks

Rohit Chauhan

Home Perspective The Value Of lsquoOvervaluedrsquo Stocks | JUN 01 2018

There is obviously no single way of making money in the stock market There are short term

traders buy and hold guys debt specialists and all kinds of people in-between Each

approach has its strengths and weaknesses and no one can claim that a specific approach is

inherently superior to the other unless they are equally proficient in both

I have come to realise that the most important factor to long term success is to understand

which approach suits your temperament

The value of learning

Some of you who have followed me on my blog would have noticed that I try not be

dogmatic about any specific style I have tried multiple approaches and continue to do so I

do have a dominant style which suits my temperament mdash buy decent quality companies and

SIGN IN SUBSCRIBE

Outlook Traveller Business Money Images Hindi



hold them for the long run but I have tried deep value arbitrage options and all other types

of investing

Most of my experiments have been failures (see here and here) from a monetary

perspective but they have deepened my understanding on what works and does not work

for me

A valid question would be why bother Why not find an approach which works for you and

then just stick with it (and maybe even publicly defend it as your faith)

Letrsquos consider an analogy Letrsquos say you are a sculptor who likes to make figures using wood

stone and other materials Letrsquos assume you are exceptionally good at making stone

sculptures but not so great on wood You go to an exhibition and see some great wood

figures and happen to meet the artist The artist tells you about his techniques and the tools

he uses Assuming you want to get better on wood will you start laughing at this artist and

belittle his tools

In a similar fashion if you are a deep value investor what should be your reaction to the

success of investors who buy and hold seemingly overvalued stocks

Durable success

I know what the first objection is to this line of thinking mdash the success of these investors is

just dumb luck These guys are not really practicing value investing but a form of

momentum investing It is just that the momentum has lasted for five years in some of these

cases and sooner or later this bubble would burst

My counterpoint sure that is possible but what if this bubble has lasted for 10-15 years in

some cases Will you still just wave away these anomalies and label them as flukes

I prefer to take a different approach There is no religious debate to this in my mind mdash if

something has worked for 3+ years in the stock market then it is worthy of investigation A

lot of bubbles and temporary fads usually get washed out in 2-3 years and so 3 years is good

cut-off point

Why not 5 years Well now we are moving from the physical to the meta-physical and

debating the nature of reality

So what can one learn from this oddity where some companies manage to sell for seemingly

high valuations for a very long time

New business model or value capture

I think the first point to look for is whether there is a change occurring in the business



modeldesign wherein due to changing customer needs and priorities a new type of design

is now more suited to meet them more profitably

I would recommend reading the book ndash Value Migration which goes over this concept in

quite a bit of detail The main point is that changing customer needs and priorities cause a

change in the business design best suited to meet them Companies which can identify and

develop a business model to meet this new reality are able to accrue a lot of value for their

shareholders

For example a rise in the income levels has caused the retail consumer to now value quality

brand image and convenience in addition to the price As a result companies which can

meet this new set of needs have been able to create a lot of value

It is easy to see this phenomenon around us mdash bathroom fittings automotive batteries

garments etc Some of these products were commodities in the past sold largely based on

price However increasing consumer purchasing power has meant that the priorities have

shifted beyond price Companies which have been able to adapt their business model to

deliver on these new priorities of brand quality and convenience in addition to price have

delivered exceptional returns Example Cera Sanitary Amara Raja Astral Poly etc

Opportunity size with durability

It is not sufficient to be able to meet the changing needs of the consumer better than the

competition For starters the opportunity size should be large so that the company can

grow for a long time to come

This is a major advantage of the Indian markets over almost all other foreign markets Even

niches in India have a market size running to millions of consumers and hence a company

which can build a good business model can easily grow for years to come

An additional point to keep in mind is the need for the company to develop a durable

competitive advantage Letrsquos take the case of the telecom industry in the early 2000s The

need for communication and mobile telephony was recognised by a few companies such as

Airtel in the late 90s and these companies moved in quickly to satisfy the needs

The market size was in the 100s of millions and most of the telecom companies were able to

scale rapidly However the edge or competitive advantage turned out to be transitory and as

a result after a few years of high profitability we soon had a lot of price-based competition

As a result by 2007-08 most companies were losing money and did not create (actually

destroyed) wealth

In such cases seemingly overvalued companies were truly overvalued

THE BIG STORY SPECIALS PERSPECTIVE PIXTORY ENTERPRISE STRATEGY MARKETS CEST LA VIE

EVENTS

Search Here



Kings of their domain

A productive area for finding multi-baggers is in the microcap space where the company

operates in a niche and is growing rapidly as its business model is uniquely suited for that

niche In addition the niche is large enough for the company to grow for a long time yet not

so big that it attracts large companies initially

There are a few examples which come to my mind Think of air coolers a few years back

(Symphony) CPVC pipes (Astral Poly) or various niche in pharma and information

technology

A small company develops a unique set of skills for this specific segment and is able to

dominate and grow within the segment for a long time In addition as the niche is quite

small it does not attract much competition till it reaches a certain size

However by the time the niche is big enough to catch the attention of larger companies in

the overall space it is too late as the specific company has established a dominant

competitive position and cannot be dislodged

A lot of these companies appear to be overpriced after they have started growing but this

ignores the possibility of above average growth and a dominant position for the company

Capacity to suffer

This is a term used by Thomas Russo (see the talk here) to describe companies which are

capable and willing to make investments in the business for the long term even though it

penalises the profit in the short term

In most cases due to market pressures companies are not willing to hurt short-term

profitability to build the business for the long term and hence the few companies which are

willing to do so appear to be overvalued due to depressed profits

Look at the example of Bajaj Corp (an old holding which I have since exited) The company

acquired the No-Marks brand in 2013 and started deducting the brand value on their PampL

account In reality the brand value was actually going up as the company continued to spend

heavily on advertising (17 of sales) and hence the profit was understated

The market did not like this short-term penalty and punished the stock in 2013 The stock

price has since recovered and we have a company which appeared to be overvalued due to

the high investments in the business

Platform Business

This link leads to a good note on what is a platform business



I do not have an example in the Indian market but will try to explain this using the example

of a well know US company It is 2004 and a company called Google decides to launch its

IPO at a then PE of around 65 A cursory look shows the company to be grossly overvalued

and as a result most of the value investors tend to give it a pass

The company has since then delivered a return of around 26 compounded and I am sure

this qualifies as a great return So why did a company which appeared so overvalued turn

out to be a 10-bagger

My own understanding is that this result came about from multiple factors To begin with

the company operates in a winner-take-all kind of a market where the No1 company tends

to dominate and capture almost all of its value Once Google had 60+ market share the

network effects kicked in and the company just kept getting more dominant in the search

space

Once this base was built the company extended it to other platforms such as mobile where

the next leg of growth has kicked in These types of companies also have a very low marginal

cost of production and hence any growth beyond a threshold drops straight to the bottom

line

This however does not explain fully the reason behind its success We have a management

which in the words of Prof Bakshi in this note are intelligent fanatics and also have the

capacity to suffer (as referenced by Thomas Russo) As a result they have continuously

invested in long-term ideas (called as moonshots) even if it meant losses in the near term

YouTube Android etc which are now bearing fruit were drains at one point of time

Such companies have been referred as platform companies and usually appear highly

overvalued in the early stages of growth Another similar company seems to be Facebook

A point of caution for every successful platform company there are atleast 10 pretenders

which destroy value So it is not easy to identify such companies ex-ante (atleast for me)

Rate of change matters

Let me introduce a new concept business clock speed which I read here This is the rate at

which a business is changing For example the rate of change in the social media business is

high and conversely there are businesses such as paints or undergarments where the rate of

change is low

I think it is quite obvious that businesses with low rate of change can create durable

competitive advantage for the long term and hence a seemingly high price turns out to be

cheap



Is the company overvalued simply because the management is investing in the business

for the long term which has suppressed the near term profits

Is the company developing a new business model which meets the changing

requirements of the consumer much better than competition

Does the company have a durable advantage and a large opportunity space (the case for a

lot of FMCG companies in India)

Does the company have network effects or is it a platform company run by an intelligent

fanatic

Has the company identified and developed a unique business model for a niche which it

will dominate for a long time

On the contrary very few high change businesses (Google Facebook being a few

exceptions) turn out to justify their sky high valuations It is difficult to establish a strong

competitive position in an industry where the basis of competition keeps changing every few

years Just look at IBM which has had to re-invent itself almost every decade to stay in

business and grow its value For every IBM there is DEC or Sun Microsystems which did

not make it

It is quite rare

It is important to understand at this point that it is quite rare to find overvalued companies

which in hindsight turn out to be undervalued A lot of overvalued companies actually turn

out to be just that and so it is important for a value-minded investor to be cautious about

such companies

In addition it is not easy to identify such companies upfront (there are no simple screens

for it) and one has to think deeply to develop the right insights to buy and hold such

companies

So why study

As I stated in the beginning of this note mdash if you want to be a successful investor it is

important to have as many mental models in your head Investing in cheap low valuation

companies is one such mental model However this does not mean one should just wave

away any company which is selling at a high price

The advantage of understanding the drivers of success is that the next time when you are

evaluating a company it makes sense to check if this company fits into any of these models

One can ask some of these questions



My post above does not cover all possible reasons why a seemingly overvalued company

will turn out to be cheap There is no standard formula or screen which will give you the

answers One has to study the company and the industry deeply to develop any useful

insights (as fuzzy as they may be)

Inspite the odds if however if you do manage to get it right it would be stupid to sell the

company based on a PE ratio which appears higher than normal

Stocks discussed in this post are for educational purpose only and not

recommendations to buy or sell Please read disclaimer towards the end of

valueinvestorindiablogspotcom The writer is a value investor and tweets

at rohitchauhan

Heres your chance to read the latest issue of Outlook Business for free Download theOutlook Magazines app now Available on Play Store and App Store

ROHIT CHAUHAN OVERVALUED STOCKS VALUE MIGRATION AIRTEL THOMAS RUSSOSANJAY BAKSHI GOOGLE YOUTUBE FACEBOOK

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Recommend

642018 This investor rivals Warren Buffett mdash and you probably havenrsquot heard of him - MarketWatch

httpswwwmarketwatchcomstorythis-investor-rivals-warren-buffett-and-you-probably-havent-heard-of-him-2018-05-30print 15

Opinion This investor rivals Warren Buffett mdashand you probably havenrsquot heard of himBy Glen ArnoldPublished May 31 2018 1140 am ET

The Berkshire Hathaway CEO so admired Lou Simpson that he suggested the Geico CIO could step in for him if needed

Bloomberg

Lou Simpson pictured in 2011

Geico is probably the best investment Warren Buffett ever made Much is due to the terrific performance of the insurerrsquosunderwriters But what turbocharged his return is the investment record of GEICOrsquos chief investment officer

Lou Simpsonrsquos record at Geico from 1979 to 2010 rivals that of Buffett at Berkshire Hathaway BRKA +070 BRKB+037 but he remains little-known except by true Buffett fans

Despite their different investment choices Simpson now 81 years old and Buffett in many ways have similar investmentphilosophies Buffett so admired Simpson that he suggested at one time that the Geico CIO could step in shouldsomething happen to himself and Charlie Munger For his part Simpson said his smaller portfolio gave him an advantageover Buffett While they were both running concentrated portfolios of less than 15 to 20 shares (often seven companies orless) Buffett had to manage up to $40 billion whereas Simpson usually had less than $4 billion

Like Buffett Simpson developed his investment approach through trial and error evolving over decades Earlier in hiscareer long before being hired by Geico he was a ldquogrowth investorrdquo often failing to properly consider whether that growthwas being offered at a reasonable price He was aiming for spectacular returns from a few star performers hoping that hehad guessed the future correctly

But through bitter experience he learned that good long-run results come from buying companies with established highperformance (rather than mere promises of future riches) with low risk and at a low price

Today many people can crunch the companyrsquos numbers and determine whether the share price looks cheap But theyneed to be equally sharp in judging qualitative factors he told an audience at Northwestern Universityrsquos Kellogg School ofManagement in November 2017

ldquoAs Warren used to tell me ldquoYoursquore better off being approximately right than exactly wrongrdquo For example one thing youneed to determine is Are the companyrsquos leaders honest Do they have integrity Do they have huge turnover Do they



treat their people poorly Does the CEO believe in running the business for the long term or is he or she focused on thenext quarterrsquos consensus earningsrdquo

Buffett highlighted Simpsonrsquos impressive performance data from 1980 through 2004 in his 2004 letter to shareholdersMost fund managers would consider themselves well ahead of the pack if they delivered an annual averageoutperformance of a mere 1 percentage point Simpson outperformed by a stunning 68 percentage points over a 25-year span

Geicorsquos equity portfolio gained an average of 203 a year compared to the SampP 500rsquos 135 SPX +108 Put anotherway a $10000 investment compounded at a 135 annual rate becomes $237081 after 25 years at a 203 annualrate it becomes $1015408

Of course all investors have years where they underperform the market Simpson underperformed for three years in arow As a value investor Simpson was out of step with the irrational exuberance of the late 1990s dot-com boom But hestuck to his principles and delivered great results in the years following the 2000 crash

Here are five key principles that helped Simpson in his quest for outperformance

Read (all day if you can)Simpson has a voracious appetite for financial newspapers other intelligent press annual reports industry reports andgenerally reads five to eight hours a day He like Buffett is not trading-intensive but reading-intensive and thought-intensive

Think independentlyBe skeptical of conventional wisdom Obtain your own information and do your own analysis Donrsquot get caught up in wavesof irrational behavior and emotion Be willing to consider unpopular and unloved companies as they often offer the greatestopportunities

Make few investments Hold them for a long timeSimpson continues to invest through SQ Advisors where he is chairman Good investment ideas mdash companies that meethis investment criteria mdash are hard to find So when he finds one he makes a large commitment

Typically SQ Advisors adds just one or two investments a year to a portfolio of 10 to 15 stocks and drops one or two hetold that Northwestern audience And sometimes the best plan is to do nothing

SQ Advisorsrsquo holdingsCompany Ticker Industry Shares held as of

March 31(thousands)

Value as ofMarch 31

($millions)

Total return -2018 through

May 25Allison TransmissionHoldings Inc

ALSN+133

TrucksConstructionFarmMachinery

8899 $3476 0

Brookfield AssetManagement IncClass A

BAMA+043

Investment Managers 8839 $3447 -4

Charles Schwab Corp SCHW+200

InvestmentBanksBrokers

5960 $3112 12

CarMax Inc KMX+141

Specialty Stores 4948 $3065 5

Liberty Global PLCClass C

LBTYK+267

CableSatellite TV 9573 $2913 -18

Cable One Inc CABO+035


Apple Inc AAPL+180

TelecommunicationsEquipment

1209 $2028 12

Sensata TechnologiesHolding PLC

ST+213

ElectronicEquipmentInstruments

3880 $2010 2

Tyler Technologies Inc TYL+003

Data Processing Services 878 $1853 29

CharterCommunications Inc

CHTR+032




Class ABerkshire HathawayInc Class B

BRKB+037

Multi-Line Insurance 798 $1591 -2

Liberty BroadbandCorp Class C

LBRDK-025

SpecialtyTelecommunications

1596 $1368 -16

Axalta CoatingSystems Ltd

AXTA+119

Industrial Specialties 32 $0971 0

SBA CommunicationsCorp Class A

SBAC+026

Real Estate InvestmentTrusts

5 $0876 -3

Hexcel Corp HXL+089

Aerospace amp Defense 5 $0339 16

Source SEC 13-F filing for March 31 2018 FactSetSimpson admits that mastering inactivity is difficult to do because it ldquois very boringrdquo but it is often the right thing to do

ldquoWarren used to say you should think of investing as somebody giving you a fare card with 20 punches Each time youmake a change punch a hole in the card Once you have made your 20th change you have to stick with what you ownThe point is just to be very careful with each decision you make The more decisions you make the higher the chancesare that you will make a poor decisionrdquo he said at Northwestern

Buy at a reasonable priceLook at the rate of return on shareholdersrsquo money used within the business If it is high and sustainable given the strategicposition of the company and the quality of management then there is a good chance of long-run appreciation in the shareprice Cash-flow return rather than profit return can be a useful additional metric given that it is more difficult tomanipulate than profit

Once a superior business has been identified then its shares should only be bought if the price is not excessive relative toits prospects Simpson uses indicators such as earnings yield He also uses the ratio of price to free cash flow

Sell your mistakes and hold the successesInvestors have a tendency to hold on to losing shares mdash they might come back and who wants to crystallize a loss mdashwhile selling early those that are performing well

Simpson summed up his opposition to these notions this way during his talk at Northwestern ldquoOne thing a lot of investorsdo is they cut their flowers and water their weeds They sell their winners and keep their losers hoping the losers willcome back even Generally itrsquos more effective to cut your weeds and water your flowers Sell the things that didnrsquot workout and let the things that are working out runhellipIf Irsquove made one mistake in the course of managing investments it wasselling really good companies too soon Because generally if yoursquove made good investments they will last for a longtimerdquo

Glen Arnold is an investor and the author of ldquoThe Deals of Warren Buffett Vol 1 The First $100 Millionrdquo

Also from Glen Arnold 4 Warren Buffett mistakes that can make you a better investor

More from MarketWatch

Damn the torpedoes mdash what could take the SampP 500 to 3000What Americarsquos gun fanatics wonrsquot tell youSampP 500 logs longest losing streak of the year as trade-war jitters weigh

We Want to Hear from YouJoin the conversation

Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM


Cycle Maturing but Not Ending

For important disclosures refer to the Disclosure Section located at the end of this report

The global expansion should continue at above-trend speed in 2H18 and

2019 driven by the ongoing capex and productivity recovery The cycle

has more room to go as we see limited signs of overheating Speed

bumps could emerge if the lift in Fed real rates causes major stress in US

corporate credit

May 8 5 PM GMT

M

4

M

Why this cycle still has more legs

An intensifying debate about the length of the global cycle Over

the last few weeks in our conversations with investors we sensed

increased concerns about the strength and duration of the global

expansion cycle A variety of reasons have been cited as concerns

The rise of protectionism risks softening data prints in DM a seem-

ingly more intense tightening in China and most recently the adverse

impact that rising US yields and an appreciating USD would have on

EM economies have added to worries that the cycle might end soon

Rising concerns stable growth Despite the emergence of these

concerns global growth has actually held up well at 4Y in 1Q18

similar to its pace in previous quarters Sequentially DM growth has

moderated but this has been offset by stronger EM growth sup-

ported by China Moreover transitory factors have impacted DM

growth in 1Q (for more details see the box on the next page) and as

the effects of these factors fade we expect sequential growth in DM

to improve

Staying constructive on the cycle From a broader perspective our

base case remains that the global economic expansion still has room

to run However as the cycle matures we do expect a slight modera-

tion in global growth to a still above-trend pace in the coming quar-

ters On an annual average basis we expect global real GDP to grow

at 39Y in 2018 and 38Y in 2019 as compared to 37Y in 2017

and 34Y in 2012-16 We see global nominal GDP (G3 and BRIC)

growing by 65Y in 2018 and 66Y in 2019 compared to 66Y in

2017

This recovery has been different from previous cycles We often

hear the argument that this expansion has been rather long and

would enter its tenth year in 2019 However the passage of time is

not the best indicator to predict when the business cycle would end

This recovery (which had been sub-par until 2016) was preceded by

a very deep recession and has been interrupted by a number of tem-

porary crises

Cycle maturing but not ending Exhibit 3

Global growth Moderating but still above trend

20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019

Global Real GDP growth Y

MS fcast

Long-term avg = 35

Source Haver Analytics Morgan Stanley Research forecasts Global is Morgan Stanley coverage excluding Argentina Venezuela Nigeria Saudi Arabia and Kazakhstan

Exhibit 4

Nominal GDP growth Stable at cycle highs

3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019

Global (G3 amp BRIC) nominal GDP growth Y

MS fcast

Source Haver Analytics Morgan Stanley Research forecasts

Exhibit 5

Morgan Stanley real GDP growth forecasts Base bull and bear cases

2017 2018E 2019E 2020-22

Base Bear Base Bull Bear Base Bull Base

GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48

China 69 62 66 68 56 64 67 56India 64 65 75 82 65 77 85 73Brazil 10 21 27 31 18 34 40 23Russia 15 -05 18 30 -10 17 31 18

Source IMF Morgan Stanley Research forecasts Note The above aggregates are PPP-weighted

M

MORGAN STANLEY RESEARCH 5

MTransitory factors affecting DM

growth in 1Q18

DM growth slowed sequentially to an estimated 16Q

SAAR from an average pace of 25 over the past four

quarters The slowdown in sequential growth was broad-

based across G4 However this moderation in growth can

be partly attributed to transitory factors In the US the

main drivers were a payback in consumption in 1Q18 after

widely publicised tax cuts and hurricane-related auto

replacement had boosted consumption in 4Q17 and

residual seasonality In the euro area issues such as tax

hikes the shifting of the timing of Easter unusually cold

weather and strikes in parts of the region partially

impacted growth In Japan consumption took a hit too in

1Q18 due to weather-related issues Moreover in some

cases the dip in high-frequency indicators appears to have

been more pronounced in the soft data (such as PMIs)

due to heady levels previously rather than in the hard

data As the impact of these transitory factors fades we

expect growth to improve from 2Q18 onwards However

the cycle is more mature in DM and there is less

economic slack than before Hence we are expecting

growth to return to a 2Q SAAR pace over the forecast

horizon as compared to 25 over the past four quarters

While growth has moved to an above-trend pace in 2017 and the

cycle is now maturing there are limited signs that the cycle will

be ending over the next 18 months Our constructive view is

informed by the following observations

1) Capex cycle not stretched productivity improvements to be sus-

tained From the perspective of a stylised business cycle we believe

that the global economy has moved from a gradual recovery phase

in 2017 to a productive growth phase (ie strong growth driven by

capex and improvements in productivity) Both capex and produc-

tivity have improved recently after a prolonged phase of post-crisis

weakness that was driven by the confluence of cyclical and structural

reasons We think that the capex cycle is not stretched as yet given

that the recovery in global investment is in its sixth quarter and

investmentGDP ratios are below previous cycle peaks We expect

global (G4 and BRIC) investment growth to improve further to 42Y

in 2018 and 43Y in 2019 from 37Y in 2017 This should sustain the

improvement in productivity growth and mitigate overheating con-

cerns Moreover there are initial signs of a structural pick-up in pro-

ductivity as digitalisation and adoption of new technology have the

potential to increase efficiency across sectors

2) No major signs of misallocation yet except in some segments of

the US private sector On aggregate in DM there has not been a sig-

nificant uptick in private sector debtGDP trends Core inflation

while rising is not yet at concerning levels However within DM

there is some concern about financial stability risks in the US given

that there has been a meaningful pick-up in leverage in parts of the

private sector particularly among corporates For EM economies

misallocation typically tends to be reflected in higher inflation and

significant widening of current account deficits However these have

remained relatively contained in EM as a whole though they are

more stretched in select EMs than others

Exhibit 6

Capex recovery supporting a revival in productivity growth

-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019

Global Real Investment Y

Global Labor Productivity Y - RS Fcast

Source Haver Analytics Conference Board Morgan Stanley Research Note Labour productivity data and forecasts from Conference Board real investment forecasts from Morgan Stanley Research

Exhibit 7

EMs ex China to be the main driver of global growth

-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China

Contribution to Global GDP Growth in ppt

MS fcast

Source Haver Analytics Morgan Stanley Research forecasts Note that DM includes countries under Morgan Stanley coverage only EMXC is Morgan Stanley coverage excluding Argentina Venezuela Nigeria Saudi Arabia and Kazakhstan

M

6

MGrowth outlook by region

DM more advanced EM catching up The global cycle is undoubt-

edly maturing But this masks important regional differences The

current cycle is clearly more advanced in DM and the US is furthest

along the cycle followed by Japan and the euro area The majority of

EMs excluding China are still in the early or mid-cycle stages of the

business cycle As regards China it is difficult to classify it according

to a traditional business cycle given its countercyclical growth

model (see below for a detailed discussion) We believe that China

will implement further tightening to address its financial risks along-

side a continuation of supply-side reforms and face a moderate slow-

down in growth as a result

Exhibit 8

G3 Private sector exits deleveraging risk attitudes improving

-5

-3

-1

1

3

5

7

9

Dec-03 Dec-05 Dec-07 Dec-09 Dec-11 Dec-13 Dec-15 Dec-17

Private Debt Growth YoY

Nominal GDP Growth YoY

G3

Source Haver Analytics Morgan Stanley Research Note Private debt includes households and non-finan-cial corporate debt

DM From balance sheet recession to self-sustaining recovery

Given the maturing economic cycle in DM we expect DM growth to

moderate somewhat to 22Y in 2018 and 20Y in 2019 from 23Y

in 2017 However this growth forecast is still stronger than the

2012-16 average economic performance of 16Y Receding head-

winds from deleveraging improving inflation expectations and nor-

malising private sector risk attitudes are supporting a recovery in

aggregate demand Stronger nominal GDP growth and improved

profitability have lifted business return expectations of the corpo-

rate sector leading to a recovery in capex spending The resulting

pick-up in productivity growth should help to sustain the DM cycle

and allow for a gradual removal of monetary policy accommodation

Exhibit 9

DMs From balance sheet recession to self-sustaining recovery

2012-16 2017-Now

Private Sectors Risk Attitudes

bull In deleveraging mode

bull Risk-averse

bull Exited deleveraging

bull Risk attitudes normal-

ised

Aggregate Demand

bull Below trend bull Above trend

Prices bull Lowflation persists bull Pricing power comes

back

Capex bull Lower return expecta-

tions weak capex

bull Return expectations

improve capex picks up

Risks

bull Premature tightening

leading to double dip

recession

bull Risk of secular stagna-

tion

bull Price and financial sta-

bility risks

Source Morgan Stanley Research

EM Chinas moderate slowdown offset by stronger growth else-

where

We expect EM growth to be 50Y in 2018 and 2019 up from 48Y

in 2017 A policy-induced slowdown in China (from 69Y in 2017 to

66Y in 2018 and 64Y in 2019) will largely be offset by an acceler-

ation in emerging markets excluding China (EMXC) growth from

36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10

China Stronger net exports contribution offsetting weaker investment

-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E

Household Consumption Govt Consumption

Investment Net Exports

Real GDP Growth

Contribution to Growth (pt)

Source CEIC Morgan Stanley Research forecasts

China Countercyclical growth model in action

Policy-makers have been on a tightening path which has raised con-

cerns about its impact on the growth trajectory

However this tightening cycle is different in three aspects from

the 2013-15 cycle (when growth slowed significantly) We assess

the pace of tightening by looking at broader credit (total social

financing) growth as our preferred metric as it covers both the impact

of monetary and fiscal (via tracking issuance of government bonds)

tightening

M


M

EMXC Still in early to mid-cycle phase of the business cycle

EMXC in recovery phase In EMs excluding China (EMXC) it was the

adjustment in the macro policy mix during 2012-16 that brought

about a turnaround in macro stability indicators Over the last few

quarters most EMXCs have moved out of the adjustment phase to

recovery As capacity utilisation has begun to improve with the sup-

port of consumption and exports we have seen a broad-based

recovery in investment growth over the last three quarters

EM fundamentals and policy mix still favourable in aggregatehellip

We assess EM fundamentals by looking at the policy mix including

real rate buffers fiscal policy and labour market policies and the

impact of this policy mix on macro stability indicators The policy mix

is still favourable at this juncture with major EMs maintaining ade-

quate real interest rate buffers staying on a path of fiscal consolida-

tion while real wage growth trends are broadly in line with real GDP

growth Moreover the inflation and current account trends for most

EMs have remained well within the central banksrsquo comfort zone

Given the favourable policy mix and early stage of the growth cycle

there is more room for growth to be sustained at close to current

levels without creating a major deterioration in macro stability indi-

cators

1 The tightening cycle has been more gradual During the

2013-15 cycle broader credit growth slowed by 930bp in a

period of 25 months In the current cycle broader credit

growth has slowed by 400bp in the past 24 months (until

March 2018)

2 The bulk of the tightening is now behind us We expect a

further cumulative deceleration in broader credit growth of

about 100bp in the next 12 months

3 This tightening is countercyclical In 2013-15 as tightening

was under way export growth continued to decelerate In this

cycle export growth has been strong Indeed as policy-

makers continue to pare back stimulus in the infrastructure

and real estate sectors net exports private investment and

consumption are providing offsets helping to support

overall growth momentum On our estimates from 2016 to

2018 the contribution of net exports to GDP growth has

swung by 120bp (from being a drag to a boost) offsetting the

decline in the contribution from investment

Given this backdrop we expect only a moderate slowdown in Chinarsquos

growth to 66Y in 2018 and China should continue to account for

about one-third of global growth in 2018

Exhibit 11

EMs ex China Adequate real rate buffers maintained

28

-4

-3

-2

-1

0

1

2

3

4

5

Mar-04 Mar-06 Mar-08 Mar-10 Mar-12 Mar-14 Mar-16 Mar-18

EMXC Real Short Rate Differentials with US point

2013 Taper

Tantrum

Source Bloomberg Haver Analytics Morgan Stanley Research Note EMXC includes Brazil India Indo-nesia Korea Mexico Poland Russia South Africa and Turkey

Exhibit 12

EMs ex China Macro stability in better shape today vs 2013

0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10

Mar-09 Mar-11 Mar-13 Mar-15 Mar-17 Mar-18

EMXC Current Account Balance as of GDP (LS)

EMXC Headline Inflation Y (RS)

2013 Taper

Tantrum

Source Haver Analytics Morgan Stanley Research Includes major countries which faced high inflationlarge external deficits before the taper tantrum (India Indonesia South Africa Turkey Brazil and Colombia)

hellipthough macro stability is relatively stretched in select EMs

Macro stability risks in the bulk of the EM universe are therefore pro-

jected to remain low to moderate though there are a few select EMs

like Turkey and Argentina which do have stretched macro stability

indicators and where some adjustment in the policy mix is necessary

In Colombia and South Africa macro stability indicators are also

somewhat more stretched relative to other EMs but have shown sig-

nificant improvement recently

M

8

MInflation Higher but no major overshoot

Global headline inflation is projected to rise given a backdrop of

a further reduction in output gaps rising oil prices and fading of tempo-

rary factors that have held core inflation down in 2017 ( Exhibit 14 )

DM core inflation rising Global core inflation is set to pick up grad-

ually over the forecast horizon The increase in underlying inflation

should mainly be driven by G3 core inflation which we expect to rise

from 13Y in 1Q18 to 16Y in 4Q18 and 18Y in 4Q19 ( Exhibit 13 )

No significant overshoot relative to central banksrsquo targets At the

same time our long-standing view is that a significant overshoot in

G3 inflation above central banksrsquo goals is less likely This is because

core inflation remains relatively low as wage growth remains more

moderate than during previous cycles and structural factors such as

technology diffusion and globalisation continue to keep upward

pressures in check

Why there are limited risks of a significant overshoot in US core

PCE price inflation In the case of the US there has been concern

that a confluence of factors ndash rising commodity prices the unem-

ployment rate moving below its long-run normal levels and past

dollar weakness ndash will lead to an overshoot in core inflation While

our forecasts suggest that core PCE should rise modestly above the

2Y goal over the forecast horizon we think that a significant over-

shoot seems less likely

First as our US team noted there are no indications of broad-

based inflationary pressures as almost the entire rise in core infla-

tion since last November has been driven by base effects in cellphone

services (the impact of last years price cuts dropping out) and price

increases in the hospital and financial services categories

Second wage growth is still moderate compared to previous

cycles and below levels that would provide major upside risks to

inflation (ie not exceeding the Fedrsquos 2Y inflation goal plus trend

labour productivity growth) ( Exhibit 15 )

Third structural factors such as technology diffusion and glo-

balisation are likely to check the rise in inflationary pressures

Indeed during 2005-07 despite the confluence of a persistent

depreciation in USD a rise in commodity prices an unemployment

rate lower than its long-run normal level and accelerating wage

growth and a rise in China non-commodity producer prices core PCE

did not overshoot 2Y by a significant magnitude ( Exhibit 16 )

Exhibit 13

G3 core inflation to pick up further

-2

-1

0

1

2

3

4

Dec-03 Dec-05 Dec-07 Dec-09 Dec-11 Dec-13 Dec-15 Dec-17 Dec-19

US Core PCE

Euro Area Core

Japan Core Core (adj for consumption tax increase)

MS fcast


Exhibit 14

Morgan Stanley inflation forecasts Base bull and bear cases

2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40

Source IMF Morgan Stanley Research forecasts Note Global and EM aggregates are calculated excluding Argentina and Venezuela

Exhibit 15

US Moderate wage growth limiting upside risks to core inflation

1

2

3

4

5

6

7

8

Mar-86 Mar-90 Mar-94 Mar-98 Mar-02 Mar-06 Mar-10 Mar-14 Mar-18

Average Hourly Earnings Y 3MMA

Compensation Per Hour Y 4QMA

Labor Productivity Y 12QMA plus 2 Inflation

Source BLS Haver Analytics Morgan Stanley Research Inflationary pressures from a tightening labour market are limited so far as wage growth remains moderate and below productivity growth (non-farm business sector output per hour in this graph) plus the 2Y inflation target

M


M

How restrictive will the Fed get As the Feds policy normalisation

process is already well under way there are concerns that further

rate hikes would lift real rates to meaningfully restrictive levels and

weigh on growth Our base case projections are that real policy rates

will reach ~02 by December 2018 and 07 by December 2019

This implies that real rates would rise above natural (r) in 1Q19 and

would be about 20bp higher than r in 4Q19 1 The key question that

arises in this context is what level of real rates would risk a major

slowdown in growth In the previous two cycles real policy rates had

risen by about 200bp above the natural rate before the expansion

ended a few quarters later In this regard considering our forecast of

actual real rates and r we project the US expansion to be sustained

through to end-2019 (we see a recession probability of 15)

1 Our estimate of the natural rate of interest (r) is 05 which is based on the

Laubach and Williams model (2003) but calculated based on our trend productivity

growth estimate of 17

EM inflation ndash rising but also not above targets on a sustained

basis Inflation in EM is set to rise too given that the ongoing eco-

nomic recovery should lead to a rise in capacity utilisation Headline

inflation will likely also rise in the near term due to higher energy

prices However for most economies we are expecting inflation to

remain within the central banksrsquo targets (or comfort zones) as the

overall policy mix remains favourable Productivity growth is recov-

ering an adequate level of real rates is being maintained fiscal policy

is still on a path of consolidation and there is no major distortion of

labour markets

Central banks on a path of policy

normalisation

DM central banks to reduce monetary accommodation As DM

growth remains relatively strong we should see a further tightening

of labour markets and rise in capacity utilisation driving core inflation

higher which should continue to encourage central banks to lean

against still easy financial conditions G4 central banks should either

continue (in the case of the Fed) or embark on a path of policy normal-

isation While we expect the ECB to end asset purchases in December

2018 and hike deposit rates in June 2019 and the BoJ to adjust the

10-year JGB yield to around 015 in 1Q19 monetary policy will still

be expansionary (see Exhibit 17 for detailed forecasts on central

bank policy actions)

Exhibit 17

Key central banks Next moves

Central Bank

Policy Action

Fed 2 more hikes in 2018 3 hikes in 2019

ECB Begin tapering asset purchases in Oct-18 ending purchases

in Dec-18 One 15bp deposit rate hike in Jun-19

BOJ Adjust 10Y JGB yield target to around 015 (0-03) in

1Q19

BOE 1 hike in 3Q18 2 hikes in 2019

PBOC Increase in bank deposit rates via liberalisation of deposit

rate caps

RBI 1 hike in 4Q18 2 hikes in 2019

BCB 25bp cut in 2Q18 125bp hike in 2019

CBR 2 more cuts in 2018 on hold in 2019

Source Morgan Stanley Research forecasts

Exhibit 16

US Core PCE did not overshoot by significant magnitude above 2Y in

2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9

Jun-03 Jun-04 Jun-05 Jun-06 Jun-07

USD TWI Y - LS leading by 18M above zero indicates USD deprecation

Average Hourly Earnings Y - RS

US Core PCE Y - RS

China Non-Commodity PPI Y (RMB) - LS leading by 14M

Unemployment Gap (RS)

Dec-07

Source CEIC Haver Analytics Morgan Stanley Research Note TWI stands for trade-weighted index Unemployment gap = actual unemployment rate minus long-run normal level

Assessing the sensitivity of higher oil prices

Given the recent rise in oil prices there has been an

increased attention on the impact higher oil prices could

have on headline inflation In this regard for the G4 +

BRIC economies we have analysed the impact of a

sustained average US$10bbl increase in Brent crude

prices relative to what futures are pricing Our analysis

suggests that headline inflation (G4 + BRIC) would be

above our baseline forecast by 20bp in 2018 and 10bp

in 2019 Importantly the pass-through to G3 core

inflation would be more moderate and occur with

somewhat of a lag raising our 2018 forecast by 5bp and

our 2019 forecast by 10bp above the baseline forecast of

an average 14Y in 2018 and 17Y in 2019

M


M

Bear Base Bull

US Ellen Zentner amp US Economics Team

Trade fears lead to a decline in investment

while volatile markets negate the benefit from

tax stimulus Additionally global growth flags

The Fed forgoes hiking in September as the bal-

ance sheet tightening triggers adverse finan-

cial market developments With incoming data

pointing to negative GDP growth in 4Q18 the

Fed begins to cut rates back towards zero as the

US enters recession and halts balance sheet

drawdown simultaneously

The expansion continues with tailwinds from

fiscal stimulus countering the effects of trade

tensions and heightened market volatility

Household consumption holds up well and

capex continues to be a source of strength

supporting productivity growth Growth accel-

erates to an average 27Y in 2018 with a

rebound in 2Q following a slow start to the

year caused by transitory factors before

slowing to 22Y in 2019

The theory of low multipliers in a late-cycle envi-

ronment does not hold Fiscal multipliers turn out

to be larger than expected and propel GDP

growth to above 3Y A non-linear Phillips curve

comes through with a vengeance and monetary

policy responds more aggressively The economy

goes through a boombust cycle that ends in US

recession by end-2019

Euro area Daniele Antonucci amp EA Economics Team

Trade policy uncertainty escalates thus

implying weaker output growth and lowering

business sentiment more generally Financial

conditions tighten which the ECB fails to offset

with a more expansionary policy ndash given a more

limited toolkit

The euro area is becoming more mid-cycle

with growth slowing from 25Y in 2017 to

~20Y on average in 2018 and 2019 With

less slack in the economy inflation continues

to rise and the ECB keep normalising policy

but more gradually than previously envisaged

Wage growth rises faster as we move into a

steeper part of the Philips curve Productivity

accelerates in a reaction to a stronger recovery in

capex Fiscal policy becomes more supportive

and boosts GDP by a more meaningful extent

Japan Takeshi Yamaguchi amp Hiromu Uezato

Weaker external demand including a US reces-

sion hurts Japanrsquos exports and capex If PM Abe

steps down due to declining Cabinet support

rates some of the policies in Abenomics could

be reversed Other downside risks include

higher oil prices andpremature policy normali-

sation by the BoJ

We retain our view that the mild economic

expansion will continue as a trend until the

next consumption tax hike in October 2019

That said we think the economy has entered

the late-cycle phase of its expansion Japan is

making a gradual exit from deflation

Japanrsquos exports and capex gain from a stronger

than-expected global recovery We see a risk of

more expansionary fiscal policy towards 2019

ahead of important national elections and the

c-tax hike PM Abe announcing a postponement of

the next c-tax is still a possibility An early snap

election could reduce political uncertainty

UK Jacob Nell

Trade talks break down (no deal) The UK

moves into a WTO relationship with the EU in

March 2019 pushing the economy into a reces-

sion and keeping the MPC on hold through the

forecast horizon

We see heightened uncertainty before a last-

minute deal for a soft Brexit Growth stalls in

the Brexit endgame in 4Q181Q19 before a

modest 2019 recovery The MPC hikes once

this year pauses until the UK has navigated

Brexit and then hikes twice in 2019

Early agreement on a soft Brexit outcome drives

a rebound in growth which holds at nearly 2Y

through 201819In this scenario we would expect

more aggressive tightening from the MPC with

the policy rate reaching 175 by end-2019

Bull-base-bear scenarios ndash DM

M

18

M

Bear Base Bull

China Robin Xing Jenny Zheng amp Zhipeng Cai

A rise in US-China trade frictionweaker-than-

expected growth in the US could drag down

Chinarsquos exports growth and a more aggressive

domestic tightening could weigh on both public

and private capex As a result GDP growth

could decelerate rapidly to 62Y in 2018 and

56Y in 2019 and CPI could be subdued at

21Y in 2018 and 19Y in 2019 amid weaker

wage growth

We expect Chinarsquos real GDP growth to moderate

from 69Y in 2017 to 66Y in 2018 and

64Y in 2019 led by weaker public and prop-

erty investment growth amid calibrated policy

tightening Meanwhile we expect a mild CPI

reflation from 16Y in 2017 to 24Y in 2018

and 25Y in 2019 led by higher core CPI and

food price normalisation

A stronger-than-expected global recovery and

milder-than-expected pace of domestic delev-

eraging could lift Chinarsquos exports and capex As

a result real GDP growth can remain resilient at

68Y in 2018 and 67Y in 2019 supporting

headline CPI at 26Y in 2018 and 28Y in

2019 close to the upper bound of the PBOCrsquos

comfort zone

India Derrick Kam Avni Jain

The financial system remains impaired and is

unable to fully support a recovery in growth

Policy uncertainty prevails in the run-up to and

post the election which coupled with weaker

trade and tighter financial conditions globally

results in businesses holding back on spending

posing a drag on growth

A synchronous recovery in consumption and

exports lifts capacity utilisation which incentiv-

ises the corporate sector to invest Moreover a

repair of corporate balance sheets and recapi-

talisation of state-owned banks leads to an

improvement in sentiment Both these factors

should pave the way for a private capex recovery

in 2018 which sets the stage for a sustained

growth cycle

The capex recovery happens at a quicker and

stronger pace due to a combination of a

stronger pick-up in demand and easing lending

conditions strengthening the growth

momentum Stronger fiscal spending ahead of

the elections would boost consumption expend-

iture particularly in rural areas

Russia Alina Slyusarchuk

External demand weakens New geopolitical

tensions result in the US adding systemic Rus-

sian SOEs to the OFAC SDN list The state

increases control over the economy and fails to

deliver micro reforms to boost growth which

translates into lower investment This keeps

uncertainty high and investment depressed Oil

price and RUB volatility translate into higher

inflation

An orthodox policy-makersrsquo response to the

new external shocks helps to stabilise the

economy Inflation averages 30Y in 2018 sup-

porting household real incomes The CBR moves

to neutral monetary policy cutting rates to

675 in 2018 The fiscal rule preserves budget

discipline and results in a federal budget surplus

at 15 of GDP

The Comprehensive Government Action Plan

with the pro-reform agenda including measures

such as infrastructure investment redistribution

of spending towards education and healthcare

as well as public service reform boosts senti-

ment supports investment and increases

potential growth Geopolitical tensions ease

Western sanctions are lifted gradually sup-

porting business confidence and growth further

Brazil Arthur Carvalho amp Thiago Machado

A non-reformist candidate wins the presidential

elections does not push forward the pension

reform and puts in place unorthodox meas-

ures This brings into question debt sustaina-

bility and puts pressure on the currency creating

strong inflationary pressures and triggering the

central bank to start hiking rates earlier than

expected impacting growth negatively

The consumer should continue to benefit from

the materially lower interest rate with some

releveraging likely in 2H18 On investment

growth although we see capex growth

remaining in positive territory we believe that

political uncertainty will have some adverse

impact Benign inflation should lead to one last

cut in May taking rates to 625 Inflation

should normalise and trigger the central bank

to hike rates again in 2019

A reformist candidate wins the presidential

elections and puts the pension reform back on

track which should lead to a pick-up in confi-

dence This would impact growth positively cre-

ating slight inflation pressures which would be

partly offset by a stronger currency The central

bank would then engage in a hiking cycle but

bring rates to a lower level as compared to our

bear case

Bull-base-bear scenarios ndash EM

M


M

A shallow rate hike cycle from 4Q18 We expect the RBI to com-

mence its rate hike cycle from 4Q18 as we think that the MPC does

have time to pause and assess more incoming data before acting in

4Q This is predicated on our view that we donrsquot expect a significant

overshoot of inflation relative to the RBIrsquos target (hence reducing the

urgencyimpetus to hike rates) and that the economic recovery will

be on a surer footing by then (as we expect private capex to show

signs of recovery) Against this backdrop of greater certainty and a

more sustained recovery in growth the central bank can then move

to commence a shallow rate hike cycle Over 2018-19 we pencil in a

total of only three rate hikes taking the terminal policy rate to 675

Risks skewed to the downside In addition to the swings in trade

and financial conditions at a global level the domestic factors of pri-

vate capex momentum and the election outcome in May 2019 would

be the key swing factors In the bull case the capex recovery happens

at a quicker and stronger pace due to a combination of a stronger

pick-up in demand and easing lending conditions strengthening the

growth momentum In the bear case the financial system remains

impaired and is unable to fully support a recovery in growth Policy

uncertainty prevails in the run-up to and post the election which cou-

pled with weaker trade and tighter financial conditions globally

should result in businesses holding back on spending posing a drag

on growth

India Towards a full-fledged recovery Derrick Kam

(852) 2239 7826

Avni Jain

(91) 6118 1850

With end demand holding up well private capex appears poised

for a recovery later this year As the economy enters into a full-

fledged recovery we expect the central bank to embark on a

shallow rate hike cycle beginning from 4Q18

We maintain our expectation for a recovery in real GDP growth to

75Y in 2018 and further to 77Y in 2019 from 64Y in 2017 More

importantly we believe that the economy is on track towards a full-

fledged recovery as we expect a recovery in private capex later this

year

Full-fledged recovery to take hold Since September 2017 eco-

nomic growth has been recovering as the economy is leaving behind

the headwinds caused by the currency replacement programme and

GST implementation Private consumption expenditure has

remained robust while exports growth despite the volatile monthly

movements has also been on a recovery path More recently we

have begun to see incipient signs of a revival in investment activity

with capital goods imports and order books of engineering and con-

struction firms posting strong growth in recent months

Looking ahead as end demand holds up well we are confident that

a recovery in private capex will be under way later this year Indeed

with the current recovery in consumption and exports capacity utili-

sation ratios have already begun to pick up rising to 741 in 4Q17

from 718 previously Corporate balance sheet fundamentals are

improving with interest rates dipping below corporate revenue

growth and also reflected in favourable trends in credit ratios (rat-

ings upgrade to downgrade ratio) Together these factors should

lead to a recovery in private capex in 2018

Temporary spike in CPI inflation Softer sequential trends in food

prices have led to weaker headline CPI inflation while core measures

of inflation have been edging up Incorporating higher oil prices and

taking on board the incoming food price trends we have revised our

forecast upwards marginally to 46Y for 2018 In the June 2018

quarter favourable base effects should kick in and lead to a tempo-

rary spike in headline inflation However these effects will likely fade

by July and we expect headline inflation to average 40Y in the

December 2018 quarter

India Forecast summary

2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77

Private consumption 83 57 74 73

Government consumption 90 111 76 76

Gross fixed investment 105 66 79 86

Contribution to GDP (pp)

Final domestic demand 88 64 74 76

Net exports 02 -08 00 01

Inventories -10 -03 00 00

Unemp rate ( labour force) NA NA NA NA

CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675

General govt balance ( GDP) -70 -67 -65 -63

Gross govt debt ( GDP) 678 667 680 680

Current account balance ( GDP) -06 -15 -16 -22

Source CSO RBI CEIC Morgan Stanley Research forecasts

682018 The Psychology of Money middot Collaborative Fund

httpwwwcollaborativefundcomblogthe-psychology-of-money 117

L

(PDF version here)

et me tell you the story of two investors neither of whom knew

each other but whose paths crossed in an interesting way

Grace Groner was orphaned at age 12 She never married She

never had kids She never drove a car She lived most of her life alone in a

one-bedroom house and worked her whole career as a secretary She was by

all accounts a lovely lady But she lived a humble and quiet life That made

the $7 million she left to charity after her death in 2010 at age 100 all the

more confusing People who knew her asked Where did Grace get all that

money

But there was no secret There was no inheritance Grace took humble

savings from a meager salary and enjoyed eighty years of hands-off

compounding in the stock market That was it

Weeks after Grace died an unrelated investing story hit the news

Richard Fuscone former vice chairman of Merrill Lynchrsquos Latin America

division declared personal bankruptcy fighting off foreclosure on two

homes one of which was nearly 20000 square feet and had a $66000 a

month mortgage Fuscone was the opposite of Grace Groner educated at

Harvard and University of Chicago he became so successful in the

investment industry that he retired in his 40s to ldquopursue personal and

charitable interestsrdquo But heavy borrowing and illiquid investments did him

in The same year Grace Goner left a veritable fortune to charity Richard

stood before a bankruptcy judge and declared ldquoI have been devastated by

the financial crisis hellip The only source of liquidity is whatever my wife is able

to sell in terms of personal furnishingsrdquo

The purpose of these stories is not to say you should be like Grace and avoid

being like Richard Itrsquos to point out that there is no other field where

these stories are even possible

In what other field does someone with no education no relevant experience

no resources and no connections vastly outperform someone with the best

education the most relevant experiences the best resources and the best

connections There will never be a story of a Grace Groner performing heart

surgery better than a Harvard-trained cardiologist Or building a faster chip

than Applersquos engineers Unthinkable

But these stories happen in investing

Thatrsquos because investing is not the study of finance Itrsquos the study of how

people behave with money And behavior is hard to teach even to really

About Investments People Blog Projects


Jun 1 2018 by Morgan Housel

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smart people You canrsquot sum up behavior with formulas to memorize or

spreadsheet models to follow Behavior is inborn varies by person is hard to

measure changes over time and people are prone to deny its existence

especially when describing themselves

Grace and Richard show that managing money isnrsquot necessarily about what

you know itrsquos how you behave But thatrsquos not how finance is typically taught

or discussed The finance industry talks too much about what to do

and not enough about what happens in your head when you try to

do it

This report describes 20 flaws biases and causes of bad behavior Irsquove seen

pop up often when people deal with money

1 Earned success and deserved failure fallacy A tendency to

underestimate the role of luck and risk and a failure to recognize

that luck and risk are different sides of the same coin

I like to ask people ldquoWhat do you want to know about investing that we canrsquot

knowrdquo

Itrsquos not a practical question So few people ask it But it forces anyone you ask

to think about what they intuitively think is true but donrsquot spend much time

trying to answer because itrsquos futile

Years ago I asked economist Robert Shiller the question He answered ldquoThe

exact role of luck in successful outcomesrdquo

I love that because no one thinks luck doesnrsquot play a role in financial

success But since itrsquos hard to quantify luck and rude to suggest peoplersquos

success is owed to luck the default stance is often to implicitly ignore luck as

a factor If I say ldquoThere are a billion investors in the world By sheer chance

would you expect 100 of them to become billionaires predominately off

luckrdquo You would reply ldquoOf courserdquo But then if I ask you to name those

investors ndash to their face ndash you will back down Thatrsquos the problem

The same goes for failure Did failed businesses not try hard enough Were

bad investments not thought through well enough Are wayward careers the

product of laziness

In some parts yes Of course But how much Itrsquos so hard to know And when

itrsquos hard to know we default to the extremes of assuming failures are

predominantly caused by mistakes Which itself is a mistake

Peoplersquos lives are a reflection of the experiences theyrsquove had and the people

theyrsquove met a lot of which are driven by luck accident and chance The line

between bold and reckless is thinner than people think and you cannot

believe in risk without believing in luck because they are two sides of the

same coin They are both the simple idea that sometimes things happen that

influence outcomes more than effort alone can achieve

After my son was born I wrote him a letter

Some people are born into families that encourage education others

are against it Some are born into flourishing economies encouraging

of entrepreneurship others are born into war and destitution I want

you to be successful and I want you to earn it But realize that not all

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success is due to hard work and not all poverty is due to laziness

Keep this in mind when judging people including yourself

2 Cost avoidance syndrome A failure to identify the true costs of

a situation with too much emphasis on financial costs while

ignoring the emotional price that must be paid to win a reward

Say you want a new car It costs $30000 You have a few options 1) Pay

$30000 for it 2) Buy a used one for less than $30000 3) Or steal it

In this case 99 of people avoid the third option because the consequences

of stealing a car outweigh the upside This is obvious

But say you want to earn a 10 annual return over the next 50 years Does

this reward come free Of course not Why would the world give you

something amazing for free Like the car therersquos a price that has to be paid

The price in this case is volatility and uncertainty And like the car you

have a few options You can pay it accepting volatility and uncertainty You

can find an asset with less uncertainty and a lower payoff the equivalent of a

used car Or you can attempt the equivalent of grand theft auto Take the

return while trying to avoid the volatility that comes along with it

Many people in this case choose the third option Like a car thief ndash though

well-meaning and law-abiding ndash they form tricks and strategies to get the

return without paying the price Trades Rotations Hedges Arbitrages

Leverage

But the Money Gods do not look highly upon those who seek a reward

without paying the price Some car thieves will get away with it Many more

will be caught with their pants down Same thing with money

This is obvious with the car and less obvious with investing because the true

cost of investing ndash or anything with money ndash is rarely the financial fee that is

easy to see and measure Itrsquos the emotional and physical price demanded by

markets that are pretty efficient Monster Beverage stock rose 211000

from 1995 to 2016 But it lost more than half its value on five separate

occasions during that time That is an enormous psychological price to pay

Buffett made $90 billion But he did it by reading SEC filings 12 hours a day

for 70 years often at the expense of paying attention to his family Here too

a hidden cost

Every money reward has a price beyond the financial fee you can see and

count Accepting that is critical Scott Adams once wrote ldquoOne of the best

pieces of advice Irsquove ever heard goes something like this If you want success

figure out the price then pay it It sounds trivial and obvious but if you

unpack the idea it has extraordinary powerrdquo Wonderful money advice

3 Rich man in the car paradox

When you see someone driving a nice car you rarely think ldquoWow the guy

driving that car is coolrdquo Instead you think ldquoWow if I had that car people

would think Irsquom coolrdquo Subconscious or not this is how people think

The paradox of wealth is that people tend to want it to signal to others that

they should be liked and admired But in reality those other people bypass

admiring you not because they donrsquot think wealth is admirable but because

they use your wealth solely as a benchmark for their own desire to be liked

and admired

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This stuff isnrsquot subtle It is prevalent at every income and wealth level There

is a growing business of people renting private jets on the tarmac for 10

minutes to take a selfie inside the jet for Instagram The people taking these

selfies think theyrsquore going to be loved without realizing that they probably

donrsquot care about the person who actually owns the jet beyond the fact that

they provided a jet to be photographed in

The point isnrsquot to abandon the pursuit of wealth of course Or even fancy

cars ndash I like both Itrsquos recognizing that people generally aspire to be respected

by others and humility graciousness intelligence and empathy tend to

generate more respect than fast cars

4 A tendency to adjust to current circumstances in a way that

makes forecasting your future desires and actions difficult

resulting in the inability to capture long-term compounding

rewards that come from current decisions

Every five-year-old boy wants to drive a tractor when they grow up Then you

grow up and realize that driving a tractor maybe isnrsquot the best career So as a

teenager you dream of being a lawyer Then you realize that lawyers work so

hard they rarely see their families So then you become a stay-at-home

parent Then at age 70 you realize you should have saved more money for

retirement

Things change And itrsquos hard to make long-term decisions when your view of

what yoursquoll want in the future is so liable to shift

This gets back to the first rule of compounding Never interrupt it

unnecessarily But how do you not interrupt a money plan ndash careers

investments spending budgeting whatever ndash when your life plans change

Itrsquos hard Part of the reason people like Grace Groner and Warren Buffett

become so successful is because they kept doing the same thing for decades

on end letting compounding run wild But many of us evolve so much over a

lifetime that we donrsquot want to keep doing the same thing for decades on end

Or anything close to it So rather than one 80-something-year lifespan our

money has perhaps four distinct 20-year blocks Compounding doesnrsquot work

as well in that situation

There is no solution to this But one thing Irsquove learned that may help is

coming back to balance and room for error Too much devotion to one goal

one path one outcome is asking for regret when yoursquore so susceptible to

change

5 Anchored-to-your-own-history bias Your personal experiences

make up maybe 000000001 of whatrsquos happened in the world

but maybe 80 of how you think the world works

If you were born in 1970 the stock market went up 10-fold adjusted for

inflation in your teens and 20s ndash your young impressionable years when you

were learning baseline knowledge about how investing and the economy

work If you were born in 1950 the same market went exactly nowhere in

your teens and 20s

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There are so many ways to cut this idea Someone who grew up in Flint

Michigan got a very different view of the importance of manufacturing jobs

than someone who grew up in Washington DC Coming of age during the

Great Depression or in war-ravaged 1940s Europe set you on a path of

beliefs goals and priorities that most people reading this including myself

canrsquot fathom

The Great Depression scared a generation for the rest of their lives Most of

them at least In 1959 John F Kennedy was asked by a reporter what he

remembered from the depression and answered

I have no first-hand knowledge of the depression My family had one

of the great fortunes of the world and it was worth more than ever

then We had bigger houses more servants we traveled more About

the only thing that I saw directly was when my father hired some

extra gardeners just to give them a job so they could eat I really did

not learn about the depression until I read about it at Harvard

Since no amount of studying or open-mindedness can genuinely recreate the

power of fear and uncertainty people go through life with totally different

views on how the economy works what itrsquos capable of doing how much we

should protect other people and what should and shouldnrsquot be valued

The problem is that everyone needs a clear explanation of how the world

works to keep their sanity Itrsquos hard to be optimistic if you wake up in the

morning and say ldquoI donrsquot know why most people think the way they dordquo

because people like the feeling of predictability and clean narratives So they

use the lessons of their own life experiences to create models of how they

think the world should work ndash particularly for things like luck risk effort

and values

And thatrsquos a problem When everyone has experienced a fraction of whatrsquos

out there but uses those experiences to explain everything they expect to

happen a lot of people eventually become disappointed confused or

dumbfounded at othersrsquo decisions

A team of economists once crunched the data on a centuryrsquos worth of

peoplersquos investing habits and concluded ldquoCurrent [investment] beliefs

depend on the realizations experienced in the pastrdquo

Keep that quote in mind when debating peoplersquos investing views Or when

yoursquore confused about their desire to hoard or blow money their fear or

greed in certain situations or whenever else you canrsquot understand why

people do what they do with money Things will make more sense

6 Historians are Prophets fallacy Not seeing the irony that

history is the study of surprises and changes while using it as a

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guide to the future An overreliance on past data as a signal to

future conditions in a field where innovation and change is the

lifeblood of progress

Geologists can look at a billion years of historical data and form models of

how the earth behaves So can meteorologists And doctors ndash kidneys

operate the same way in 2018 as they did in 1018

The idea that the past offers concrete directions about the future is

tantalizing It promotes the idea that the path of the future is buried within

the data Historians ndash or anyone analyzing the past as a way to indicate the

future ndash are some of the most important members of many fields

I donrsquot think finance is one of them At least not as much as wersquod like to

think

The cornerstone of economics is that things change over time because the

invisible hand hates anything staying too good or too bad indefinitely Bill

Bonner once described how Mr Market works ldquoHersquos got a lsquoCapitalism at

Workrsquo T-shirt on and a sledgehammer in his handrdquo Few things stay the same

for very long which makes historians something far less useful than

prophets

Consider a few big ones

The 401(K) is 39 years old ndash barely old enough to run for president The

Roth IRA isnrsquot old enough to drink So personal financial advice and analysis

about how Americans save for retirement today is not directly comparable to

what made sense just a generation ago Things changed

The venture capital industry barely existed 25 years ago There are single

funds today that are larger than the entire industry was a generation ago

Phil Knight wrote about his early days after starting Nike ldquoThere was no

such thing as venture capital An aspiring young entrepreneur had very few

places to turn and those places were all guarded by risk-averse gatekeepers

with zero imagination In other words bankersrdquo So our knowledge of

backing entrepreneurs investment cycles and failure rates is not something

we have a deep base of history to learn from Things changed

Or take public markets The SampP 500 did not include financial stocks until

1976 today financials make up 16 of the index Technology stocks were

virtually nonexistent 50 years ago Today theyrsquore more than a fifth of the

index Accounting rules have changed over time So have disclosures

auditing and market liquidity Things changed

The most important driver of anything tied to money is the stories people tell

themselves and the preferences they have for goods and services Those

things donrsquot tend to sit still They change with culture and generation And

theyrsquoll keep changing

The mental trick we play on ourselves here is an over-admiration of people

who have been there done that when it comes to money Experiencing

specific events does not necessarily qualify you to know what will happen

next In fact it rarely does because experience leads to more overconfidence

than prophetic ability

That doesnrsquot mean we should ignore history when thinking about money But

therersquos an important nuance The further back in history you look the more

general your takeaways should be General things like peoplersquos relationship

to greed and fear how they behave under stress and how they respond to

incentives tends to be stable in time The history of money is useful for that

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kind of stuff But specific trends specific trades specific sectors and specific

causal relationships are always a showcase of evolution in progress

7 The seduction of pessimism in a world where optimism is the

most reasonable stance

Historian Deirdre McCloskey says ldquoFor reasons I have never understood

people like to hear that the world is going to hellrdquo

This isnrsquot new John Stuart Mill wrote in the 1840s ldquoI have observed that not

the man who hopes when others despair but the man who despairs when

others hope is admired by a large class of persons as a sagerdquo

Part of this is natural Wersquove evolved to treat threats as more urgent than

opportunities Buffett says ldquoIn order to succeed you must first surviverdquo

But pessimism about money takes a different level of allure Say therersquos going

to be a recession and you will get retweeted Say wersquoll have a big recession

and newspapers will call you Say wersquore nearing the next Great Depression

and yoursquoll get on TV But mention that good times are ahead or markets

have room to run or that a company has huge potential and a common

reaction from commentators and spectators alike is that you are either a

salesman or comically aloof of risks

A few things are going on here

One is that money is ubiquitous so something bad happening tends to affect

everyone albeit in different ways That isnrsquot true of say weather A

hurricane barreling down on Florida poses no direct risk to 92 of

Americans But a recession barreling down on the economy could impact

every single person ndash including you so pay attention This goes for

something as specific as the stock market More than half of all households

directly own stocks

Another is that pessimism requires action ndash Move Get out Run Sell Hide

Optimism is mostly a call to stay the course and enjoy the ride So itrsquos not

nearly as urgent

A third is that there is a lot of money to be made in the finance industry

which ndash despite regulations ndash has attracted armies of scammers hucksters

and truth-benders promising the moon A big enough bonus can convince

even honest law-abiding finance workers selling garbage products that

theyrsquore doing good for their customers Enough people have been

bamboozled by the finance industry that a sense of ldquoIf it sounds too good to

be true it probably isrdquo has enveloped even rational promotions of optimism

Most promotions of optimism by the way are rational Not all of course

But we need to understand what optimism is Real optimists donrsquot believe

that everything will be great Thatrsquos complacency Optimism is a belief that

the odds of a good outcome are in your favor over time even when there will

be setbacks along the way The simple idea that most people wake up in the

morning trying to make things a little better and more productive than wake

up looking to cause trouble is the foundation of optimism Itrsquos not

complicated Itrsquos not guaranteed either Itrsquos just the most reasonable bet for

most people The late statistician Hans Rosling put it differently ldquoI am not

an optimist I am a very serious possibilistrdquo

8 Underappreciating the power of compounding driven by the

tendency to intuitively think about exponential growth in linear

terms

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IBM made a 35 megabyte hard drive in the 1950s By the 1960s things were

moving into a few dozen megabytes By the 1970s IBMrsquos Winchester drive

held 70 megabytes Then drives got exponentially smaller in size with more

storage A typical PC in the early 1990s held 200-500 megabytes

And then hellip wham Things exploded

1999 ndash Applersquos iMac comes with a 6 gigabyte hard drive

2003 ndash 120 gigs on the Power Mac

2006 ndash 250 gigs on the new iMac

2011 ndash first 4 terabyte hard drive

2017 ndash 60 terabyte hard drives

Now put it together From 1950 to 1990 we gained 296 megabytes From

1990 through today we gained 60 million megabytes

The punchline of compounding is never that itrsquos just big Itrsquos always ndash no

matter how many times you study it ndash so big that you can barely wrap your

head around it In 2004 Bill Gates criticized the new Gmail wondering why

anyone would need a gig of storage Author Steven Levy wrote ldquoDespite his

currency with cutting-edge technologies his mentality was anchored in the

old paradigm of storage being a commodity that must be conservedrdquo You

never get accustomed to how quickly things can grow

I have heard many people say the first time they saw a compound interest

table ndash or one of those stories about how much more yoursquod have for

retirement if you began saving in your 20s vs your 30s ndash changed their life

But it probably didnrsquot What it likely did was surprise them because the

results intuitively didnrsquot seem right Linear thinking is so much more

intuitive than exponential thinking Michael Batnick once explained it If I

ask you to calculate 8+8+8+8+8+8+8+8+8 in your head you can do it in a

few seconds (itrsquos 72) If I ask you to calculate 8x8x8x8x8x8x8x8x8 your

head will explode (itrsquos 134217728)

The danger here is that when compounding isnrsquot intuitive we often ignore its

potential and focus on solving problems through other means Not because

wersquore overthinking but because we rarely stop to consider compounding

potential

There are over 2000 books picking apart how Warren Buffett built his

fortune But none are called ldquoThis Guy Has Been Investing Consistently for

Three-Quarters of a Centuryrdquo But we know thatrsquos the key to the majority of

his success itrsquos just hard to wrap your head around that math because itrsquos

not intuitive There are books on economic cycles trading strategies and

sector bets But the most powerful and important book should be called

ldquoShut Up And Waitrdquo Itrsquos just one page with a long-term chart of economic

growth Physicist Albert Bartlett put it ldquoThe greatest shortcoming of the

human race is our inability to understand the exponential functionrdquo

The counterintuitiveness of compounding is responsible for the majority of

disappointing trades bad strategies and successful investing attempts Good

investing isnrsquot necessarily about earning the highest returns because the

highest returns tend to be one-off hits that kill your confidence when they

end Itrsquos about earning pretty good returns that you can stick with for a long

period of time Thatrsquos when compounding runs wild

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9 Attachment to social proof in a field that demands contrarian

thinking to achieve above-average results

The Berkshire Hathaway annual meeting in Omaha attracts 40000 people

all of whom consider themselves contrarians People show up at 4 am to wait

in line with thousands of other people to tell each other about their lifelong

commitment to not following the crowd Few see the irony

Anything worthwhile with money has high stakes High stakes entail risks of

being wrong and losing money Losing money is emotional And the desire to

avoid being wrong is best countered by surrounding yourself with people

who agree with you Social proof is powerful Someone else agreeing with

you is like evidence of being right that doesnrsquot have to prove itself with facts

Most peoplersquos views have holes and gaps in them if only subconsciously

Crowds and social proof help fill those gaps reducing doubt that you could

be wrong

The problem with viewing crowds as evidence of accuracy when dealing with

money is that opportunity is almost always inversely correlated with

popularity What really drives outsized returns over time is an increase in

valuation multiples and increasing valuation multiples relies on an

investment getting more popular in the future ndash something that is always

anchored by current popularity

Herersquos the thing Most attempts at contrarianism is just irrational cynicism

in disguise ndash and cynicism can be popular and draw crowds Real

contrarianism is when your views are so uncomfortable and belittled that

they cause you to second guess whether theyrsquore right Very few people can do

that But of course thatrsquos the case Most people canrsquot be contrarian by

definition Embrace with both hands that statistically you are one of those

people

10 An appeal to academia in a field that is governed not by clean

rules but loose and unpredictable trends

Harry Markowitz won the Nobel Prize in economics for creating formulas

that tell you exactly how much of your portfolio should be in stocks vs bonds

depending on your ideal level of risk A few years ago the Wall Street Journal

asked him how given his work he invests his own money He replied

I visualized my grief if the stock market went way up and I wasnrsquot in it

ndash or if it went way down and I was completely in it My intention was

to minimize my future regret So I split my contributions 5050

between bonds and equities

There are many things in academic finance that are technically right but fail

to describe how people actually act in the real world Plenty of academic

finance work is useful and has pushed the industry in the right direction But

its main purpose is often intellectual stimulation and to impress other

academics I donrsquot blame them for this or look down upon them for it We

should just recognize it for what it is

One study I remember showed that young investors should use 2x leverage

in the stock market because ndash statistically ndash even if you get wiped out yoursquore

still likely to earn superior returns over time as long as you dust yourself off

and keep investing after a wipeout Which in the real world no one would

actually do Theyrsquod swear off investing for life What works on a spreadsheet

and what works at the kitchen table are ten miles apart

The disconnect here is that academics typically desire very precise rules and

formulas But real-world people use it as a crutch to try to make sense of a

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messy and confusing world that by its nature eschews precision Those are

opposite things You cannot explain randomness and emotion with precision

and reason

People are also attracted to the titles and degrees of academics because

finance is not a credential-sanctioned field like say medicine is So the

appearance of a PhD stands out And that creates an intense appeal to

academia when making arguments and justifying beliefs ndash ldquoAccording to this

Harvard study helliprdquo or ldquoAs Nobel Prize winner so and so showed helliprdquo It carries

so much weight when other people cite ldquoSome guy on CNBC from an

eponymous firm with a tie and a smilerdquo A hard reality is that what often

matters most in finance will never win a Nobel Prize Humility and room for

error

11 The social utility of money coming at the direct expense of

growing money wealth is what you donrsquot see

I used to park cars at a hotel This was in the mid-2000s in Los Angeles

when real estate money flowed I assumed that a customer driving a Ferrari

was rich Many were But as I got to know some of these people I realized

they werenrsquot that successful At least not nearly what I assumed Many were

mediocre successes who spent most of their money on a car

If you see someone driving a $200000 car the only data point you have

about their wealth is that they have $200000 less than they did before they

bought the car Or theyrsquore leasing the car which truly offers no indication of

wealth

We tend to judge wealth by what we see We canrsquot see peoplersquos bank accounts

or brokerage statements So we rely on outward appearances to gauge

financial success Cars Homes Vacations Instagram photos

But this is America and one of our cherished industries is helping people

fake it until they make it

Wealth in fact is what you donrsquot see Itrsquos the cars not purchased The

diamonds not bought The renovations postponed the clothes forgone and

the first-class upgrade declined Itrsquos assets in the bank that havenrsquot yet been

converted into the stuff you see

But thatrsquos not how we think about wealth because you canrsquot contextualize

what you canrsquot see

Singer Rihanna nearly went broke after overspending and sued her financial

advisor The advisor responded ldquoWas it really necessary to tell her that if

you spend money on things you will end up with the things and not the

moneyrdquo

You can laugh But the truth is yes people need to be told that When most

people say they want to be a millionaire what they really mean is ldquoI want to

spend a million dollarsrdquo which is literally the opposite of being a millionaire

This is especially true for young people

A key use of wealth is using it to control your time and providing you with

options Financial assets on a balance sheet offer that But they come at the

direct expense of showing people how much wealth you have with material

stuff

12 A tendency toward action in a field where the first rule of

compounding is to never interrupt it unnecessarily

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If your sink breaks you grab a wrench and fix it If your arm breaks you put

it in a cast

What do you do when your financial plan breaks

The first question ndash and this goes for personal finance business finance and

investing plans ndash is how do you know when itrsquos broken

A broken sink is obvious But a broken investment plan is open to

interpretation Maybe itrsquos just temporarily out of favor Maybe yoursquore

experiencing normal volatility Maybe you had a bunch of one-off expenses

this quarter but your savings rate is still adequate Itrsquos hard to know

When itrsquos hard to distinguish broken from temporarily out of favor the

tendency is to default to the former and spring into action You start fiddling

with the knobs to find a fix This seems like the responsible thing to do

because when virtually everything else in your life is broken the correct

action is to fix it

There are times when money plans need to be fixed Oh are there ever But

there is also no such thing as a long-term money plan that isnrsquot susceptible to

volatility Occasional upheaval is usually part of a standard plan

When volatility is guaranteed and normal but is often treated as something

that needs to be fixed people take actions that ultimately just interrupts the

execution of a good plan ldquoDonrsquot do anythingrdquo are the most powerful words

in finance But they are both hard for individuals to accept and hard for

professionals to charge a fee for So we fiddle Far too much

13 Underestimating the need for room for error not just

financially but mentally and physically

Ben Graham once said ldquoThe purpose of the margin of safety is to render the

forecast unnecessaryrdquo

There is so much wisdom in this quote But the most common response even

if subconsciously is ldquoThanks Ben But Irsquom good at forecastingrdquo

People underestimate the need for room for error in almost everything they

do that involves money Two things cause this One is the idea that your view

of the future is right driven by the uncomfortable feeling that comes from

admitting the opposite The second is that yoursquore therefore doing yourself

economic harm by not taking actions that exploit your view of the future

coming true

But room for error is underappreciated and misunderstood Itrsquos often viewed

as a conservative hedge used by those who donrsquot want to take much risk or

arenrsquot confident in their views But when used appropriately itrsquos the opposite

Room for error lets you endure and endurance lets you stick around long

enough to let the odds of benefiting from a low-probability outcome fall in

your favor The biggest gains occur infrequently either because they donrsquot

happen often or because they take time to compound So the person with

enough room for error in part of their strategy to let them endure hardship

in the other part of their strategy has an edge over the person who gets wiped

out game over insert more tokens when theyrsquore wrong

There are also multiple sides to room for error Can you survive your assets

declining by 30 On a spreadsheet maybe yes ndash in terms of actually paying

your bills and staying cash-flow positive But what about mentally It is easy

to underestimate what a 30 decline does to your psyche Your confidence

may become shot at the very moment opportunity is at its highest You ndash or

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your spouse ndash may decide itrsquos time for a new plan or new career I know

several investors who quit after losses because they were exhausted

Physically exhausted Spreadsheets can model the historic frequency of big

declines But they cannot model the feeling of coming home looking at your

kids and wondering if yoursquove made a huge mistake that will impact their

lives

14 A tendency to be influenced by the actions of other people who

are playing a different financial game than you are

Cisco stock went up three-fold in 1999 Why Probably not because people

actually thought the company was worth $600 billion Burton Malkiel once

pointed out that Ciscorsquos implied growth rate at that valuation meant it would

become larger than the entire US economy within 20 years

Its stock price was going up because short-term traders thought it would

keep going up And they were right for a long time That was the game they

were playing ndash ldquothis stock is trading for $60 and I think itrsquoll be worth $65

before tomorrowrdquo

But if you were a long-term investor in 1999 $60 was the only price available

to buy So you may have looked around and said to yourself ldquoWow maybe

others know something I donrsquotrdquo And you went along with it You even felt

smart about it But then the traders stopped playing their game and you ndash

and your game ndash was annihilated

What you donrsquot realize is that the traders moving the marginal price are

playing a totally different game than you are And if you start taking cues

from people playing a different game than you are you are bound to be

fooled and eventually become lost since different games have different rules

and different goals

Few things matter more with money than understanding your own time

horizon and not being persuaded by the actions and behaviors of people

playing different games

This goes beyond investing How you save how you spend what your

business strategy is how you think about money when you retire and how

you think about risk may all be influenced by the actions and behaviors of

people who are playing different games than you are

Personal finance is deeply personal and one of the hardest parts is learning

from others while realizing that their goals and actions might be miles

removed from whatrsquos relevant to your own life

15 An attachment to financial entertainment due to the fact that

money is emotional and emotions are revved up by argument

extreme views flashing lights and threats to your wellbeing

If the average Americarsquos blood pressure went up by 3 my guess is a few

newspapers would cover it on page 16 nothing would change and wersquod move

on But if the stock market falls 3 well no need to guess how we might

respond This is from 2015 ldquoPresident Barack Obama has been briefed on

Mondayrsquos choppy global market movementrdquo

Why does financial news of seemingly low importance overwhelm news that

is objectively more important

Because finance is entertaining in a way other things ndash orthodontics

gardening marine biology ndash are not Money has competition rules upsets

wins losses heroes villains teams and fans that makes it tantalizingly close

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to a sporting event But itrsquos even an addiction level up from that because

money is like a sporting event where yoursquore both the fan and the player with

outcomes affecting you both emotionally and directly

Which is dangerous

It helps Irsquove found when making money decisions to constantly remind

yourself that the purpose of investing is to maximize returns not minimize

boredom Boring is perfectly fine Boring is good If you want to frame this

as a strategy remind yourself opportunity lives where others arenrsquot and

others tend to stay away from whatrsquos boring

16 Optimism bias in risk-taking or ldquoRussian Roulette should

statistically workrdquo syndrome An over attachment to favorable

odds when the downside is unacceptable in any circumstance

Nassim Taleb says ldquoYou can be risk loving and yet completely averse to

ruinrdquo

The idea is that you have to take risk to get ahead but no risk that could wipe

you out is ever worth taking The odds are in your favor when playing

Russian Roulette But the downside is never worth the potential upside

The odds of something can be in your favor ndash real estate prices go up most

years and most years yoursquoll get a paycheck every other week ndash but if

something has 95 odds of being right then 5 odds of being wrong means

you will almost certainly experience the downside at some point in your life

And if the cost of the downside is ruin the upside the other 95 of the time

likely isnrsquot worth the risk no matter how appealing it looks

Leverage is the devil here It pushes routine risks into something capable of

producing ruin The danger is that rational optimism most of the time masks

the odds of ruin some of the time in a way that lets us systematically

underestimate risk Housing prices fell 30 last decade A few companies

defaulted on their debt This is capitalism ndash it happens But those with

leverage had a double wipeout Not only were they left broke but being

wiped out erased every opportunity to get back in the game at the very

moment opportunity was ripe A homeowner wiped out in 2009 had no

chance of taking advantage of cheap mortgage rates in 2010 Lehman

Brothers had no chance of investing in cheap debt in 2009

My own money is barbelled I take risks with one portion and am a terrified

turtle with the other This is not inconsistent but the psychology of money

would lead you to believe that it is I just want to ensure I can remain

standing long enough for my risks to pay off Again you have to survive to

succeed

A key point here is that few things in money are as valuable as options The

ability to do what you want when you want with who you want and why

you want has infinite ROI

17 A preference for skills in a field where skills donrsquot matter if

they arenrsquot matched with the right behavior

This is where Grace and Richard come back in There is a hierarchy of

investor needs and each topic here has to be mastered before the one above

it matters

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Richard was very skilled at the top of this pyramid but he failed the bottom

blocks so none of it mattered Grace mastered the bottom blocks so well that

the top blocks were hardly necessary

18 Denial of inconsistencies between how you think the world

should work and how the world actually works driven by a desire

to form a clean narrative of cause and effect despite the inherent

complexities of everything involving money

Someone once described Donald Trump as ldquoUnable to distinguish between

what happened and what he thinks should have happenedrdquo Politics aside I

think everyone does this

There are three parts to this

You see a lot of information in the world

You canrsquot process all of it So you have to filter

You only filter in the information that meshes with the way you think the

world should work

Since everyone wants to explain what they see and how the world works with

clean narratives inconsistencies between what we think should happen and

what actually happens are buried

An example Higher taxes should slow economic growth ndash thatrsquos a common

sense narrative But the correlation between tax rates and growth rates is

hard to spot So if you hold onto the narrative between taxes and growth

you say there must be something wrong with the data And you may be right

But if you come across someone else pushing aside data to back up their

narrative ndash say arguing that hedge funds have to generate alpha otherwise

no one would invest in them ndash you spot what you consider a bias There are a

thousand other examples Everyone just believes what they want to believe

even when the evidence shows something else Stories over statistics

Accepting that everything involving money is driven by illogical emotions

and has more moving parts than anyone can grasp is a good start to

remembering that history is the study of things happening that people didnrsquot

think would or could happen This is especially true with money

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19 Political beliefs driving financial decisions influenced by

economics being a misbehaved cousin of politics

I once attended a conference where a well known investor began his talk by

saying ldquoYou know when President Obama talks about clinging to guns and

bibles That is me folks And Irsquom going to tell you today about how his

reckless policies are impacting the economyrdquo

I donrsquot care what your politics are there is no possible way you can make

rational investment decisions with that kind of thinking

But itrsquos fairly common Look at what happens in 2016 on this chart The rate

of GDP growth jobs growth stock market growth interest rates ndash go down

the list ndash did not materially change Only the president did

Years ago I published a bunch of economic performance numbers by

president And it drove people crazy because the data often didnrsquot mesh with

how they thought it should based on their political beliefs Soon after a

journalist asked me to comment on a story detailing how statistically

Democrats preside over stronger economies than Republicans I said you

couldnrsquot make that argument because the sample size is way too small But

he pushed and pushed and wrote a piece that made readers either cheer or

sweat depending on their beliefs

The point is not that politics donrsquot influence the economy But the reason this

is such a sensitive topic is because the data often surprises the heck out of

people which itself is a reason to realize that the correlation between politics

and economics isnrsquot as clear as yoursquod like to think it is

20 The three-month bubble Extrapolating the recent past into

the near future and then overestimating the extent to which

whatever you anticipate will happen in the near future will impact

your future

News headlines in the month after 911 are interesting Few entertain the

idea that the attack was a one-off the next massive terrorist attack was

certain to be around the corner ldquoAnother catastrophic terrorist attack is

inevitable and only a matter of timerdquo one defense analyst said in 2002 ldquoA

top counterterrorism official says itrsquos lsquoa question of when not ifrdquo wrote

another headline Beyond the anticipation that another attack was imminent

was a belief that it would affect people the same way The Today Show ran a

segment pitching parachutes for office workers to keep under their desks in

case they needed to jump out of a skyscraper

Believing that what just happened will keep happening shows up constantly

in psychology We like patterns and have short memories The added feeling

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Highlight



that a repeat of what just happened will keep affecting you the same way is

an offshoot And when yoursquore dealing with money it can be a torment

Every big financial win or loss is followed by mass expectations of more wins

and losses With it comes a level of obsession over the effects of those events

repeating that can be wildly disconnected from your long-term goals

Example The stock market falling 40 in 2008 was followed uninterrupted

for years with forecasts of another impending plunge Expecting what just

happened to happen soon again is one thing and an error in itself But not

realizing that your long-term investing goals could remain intact unharmed

even if we have another big plunge is the dangerous byproduct of recency

bias ldquoMarkets tend to recover over time and make new highsrdquo was not a

popular takeaway from the financial crisis ldquoMarkets can crash and crashes

suckrdquo was despite the former being so much more practical than the latter

Most of the time something big happening doesnrsquot increase the odds of it

happening again Itrsquos the opposite as mean reversion is a merciless law of

finance But even when something does happen again most of the time it

doesnrsquot ndash or shouldnrsquot ndash impact your actions in the way yoursquore tempted to

think because most extrapolations are short term while most goals are long

term A stable strategy designed to endure change is almost always superior

to one that attempts to guard against whatever just happened happening

again

If therersquos a common denominator in these itrsquos a preference for humility

adaptability long time horizons and skepticism of popularity around

anything involving money Which can be summed up as Be prepared to roll

with the punches

Jiddu Krishnamurti spent years giving spiritual talks He became more

candid as he got older In one famous talk he asked the audience if theyrsquod

like to know his secret

He whispered ldquoYou see I donrsquot mind what happensrdquo

That might be the best trick when dealing with the psychology of money

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Jun 1 2018 by Morgan Housel middot morganhousel

Email address Submit

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Please refer to important disclosures at the end of this report

`

Equity Research May 29 2018

Nifty 50 10633

ICICI Securities Limited is the author and distributor of this report

Cashless status report Cash is back CIC at 116 of GDP (18-Mayrsquo18) ndash back in range

Cashless transactions (ex-RTGS) continue to rise

Previous report ldquoTez-i in digital paymentsrdquo

Strategy

Cashless transactions continue their uptrendhellip so does cash in circulation

116

4

6

8

10

12

14

Jan

11

May 1

1

Se

p 1

1

Jan

12

May 1

2

Se

p 1

2

Jan

13

May 1

3

Se

p 1

3

Jan

14

May 1

4

Se

p 1

4

Jan

15

May 1

5

Se

p 1

5

Jan

16

May 1

6

Se

p 1

6

Jan

17

May 1

7

Se

p 1

7

Jan

18

May 1

8

CIC as a of GDP

0

200

400

600

800

1000

1200

1400

1600

Ap

r1

1

Se

p1

1

Feb1

2

Jul1

2

Dec1

2

May1

3

Oct1

3

Mar14

Au

g1

4

Jan

15

Jun

15

Nov1

5

Ap

r1

6

Se

p1

6

Feb1

7

Jul1

7

Dec1

7


72

Research Analysts

Vinod Karki vinodkarkiicicisecuritiescom +91 22 6637 7586

Siddharth Gupta siddharthguptaicicisecuritiescom +91 22 2277 7607

As the transient effects of demonetisation fade we analyse the latest trends in Indiarsquos move toward a cashless economy which incidentally was one of the stated objectives of demonetisation Key trends observed are

Cash levels in the economy did not decrease permanently After dipping significantly post demonetisation cash in circulation (CIC) at Rs1933tn is back to the trend growth seen in the pre-demonetisation period which has resulted in CIC as a percentage of GDP inch closer to the pre-demonetisation level of ~12

Value of cash withdrawals from ATMs has risen back to pre-demonetisation period at ~Rs25trn per monthhellip In a trend reversal the amount of cash withdrawn from bank accounts via ATMrsquos has been inching up and is now comparable to trends seen pre-demonetisation

hellipalthough number of cash withdrawals continues to be below trend implying higher cash withdrawals per transaction at ATMs As ATM transaction above a certain level (varies from bank to bank) are charged by banks the quantum of cash withdrawal per ATM transaction has increased

Despite rising CIC overall cashless transactions value (ex-RTGS) continues to grow at a faster pace than in pre demonetisation periodhellip Overall cashless transactions (ex-RTGS) hit Rs828trn in Q4FY18 a robust 23 growth on the high base of last year It indicates that the growth in electronic digital transactions is a permanent and irreversible trend

hellipdriven by NEFT IMPS UPI and cards at POS Rise in cashless transactions is driven by NEFT (Rs18trnmonth) IMPS (Rs1trnmonth) UPI (Rs230bnmonth) and card transactions (Rs810bnmonth) growing YoY by 37 82 976 and 13 respectively

RBIrsquos KYC norms puts brake on the exponential rise of M-Wallets transaction value M-Wallets transaction value grew exponentially from a pre- demonetisation base of Rs33bnmonth to Rs130bn in Febrsquo18 but RBIrsquos KYC (Know your Customer) norms post Febrsquo18 have resulted in reversal in the value of M-Wallet transactions which fell to Rs100bn in Marrsquo18

POS terminals continue to rise along with number of cards issued by banks while ATM growth plateaus Significant ramp-up by e-commerce players banks and retail players has resulted in 2590 POS per million persons up from 1250 from the pre-demonetisation period Credit cards outstanding grew a robust 26 for Q4FY18 and the number outstanding is 37mn at Marrsquo18-end On the other hand the number of ATMs per million persons has remained flat at 184 since demonetisation while Paper clearing is seeing a decline in transactions by value

Private sector banks have a distinct edge over their PSU counterparts in terms of electronic transactions but the reverse is true for ATM networks and cash transactions at ATMs To contextualise the impact of digital transactions the share of internet and mobile transactions initiated by customers moved up to 85 in FY18 from 3 in FY08 for HDFC Bank while during the same period the share of transactions handled by branches has fallen from 43 to 8 Overall private sector banks have an edge over PSU banks in electronic mode of transactions such as credit cards (Pvt bank share 82) and debit cards (43) usage at POS mobile banking (66) and NEFT outward (51) transactions On the other hand PSU banks have an edge in terms of cash transactions in the form of wider ATM networks (PSU share 71) and higher share of cash withdrawal from ATMs (73)

INDIA


2










0

5

10

15

20

25

Jan

-05

Jul-0

5

Jan

-06

Jul-0

6

Jan

-07

Jul-0

7

Jan

-08

Jul-0

8

Jan

-09

Jul-0

9

Jan

-10

Jul-1

0

Jan

-11

Jul-1

1

Jan

-12

Jul-1

2

Jan

-13

Jul-1

3

Jan

-14

Jul-1

4

Jan

-15

Jul-1

5

Jan

-16

Jul-1

6

Jan

-17

Jul-1

7

Jan

-18

(Rs tn

)


116

4

6

8

10

12

14

Jan

11

May 1

1

Se

p 1

1

Jan

12

Ma

y 1

2

Se

p 1

2

Jan

13

Ma

y 1

3

Se

p 1

3

Jan

14

Ma

y 1

4

Se

p 1

4

Jan

15

Ma

y 1

5

Se

p 1

5

Jan

16

Ma

y 1

6

Se

p 1

6

Jan

17

Ma

y 1

7

Se

p 1

7

Jan

18

Ma

y 1

8

CIC as a of GDP


3











00

05

10

15

20

25

30

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Ju

l12

Oct1

2

Jan

13

Ap

r1

3

Ju

l13

Oct1

3

Jan

14

Ap

r1

4

Ju

l14

Oct1

4

Jan

15

Ap

r1

5

Ju

l15

Oct1

5

Jan

16

Ap

r1

6

Ju

l16

Oct1

6

Jan

17

Ap

r1

7

Ju

l17

Oct1

7

Jan

18

(Rs trn

)


0

100

200

300

400

500

600

700

800

900

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Jul1

2

Oct1

2

Jan

13

Ap

r1

3

Jul1

3

Oct1

3

Jan

14

Ap

r1

4

Jul1

4

Oct1

4

Jan

15

Ap

r1

5

Jul1

5

Oct1

5

Jan

16

Ap

r1

6

Jul1

6

Oct1

6

Jan

17

Ap

r1

7

Jul1

7

Oct1

7

Jan

18



4






irreversible trend


Mode of Transaction




Paper Clearing 367 298 -19 22343 21308 -5


- NEFT 499 548 10 38527 52759 37

- IMPS 190 309 63 1538 2803 82




- Debit Card at POS 852 902 6 1205 1200 0



UPI 14 501 34x 60 589 89x





Mobile Banking 315 676 114 4394 3649 -17










0

5

10

15

20

25

30

35

40

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

Ma

y1

3

Oct1

3

Ma

r14

Au

g1

4

Jan

15

Jun

15

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7

(Rs tn)


55

0

200

400

600

800

1000

1200

1400

1600

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

May1

3

Oct1

3

Ma

r14

Au

g1

4

Ja

n1

5

Ju

n1

5

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7


72


5










0

50

100

150

200

250

0

5

10

15

20

25

Ap

r-11

Au

g-1

1

Dec-1

1

Ap

r-12

Au

g-1

2

Dec-1

2

Ap

r-13

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-15

Au

g-1

5

Dec-1

5

Ap

r-16

Au

g-1

6

Dec-1

6

Ap

r-17

Au

g-1

7

Dec-1

7

(mn)

(Rs tn)


0

20

40

60

80

100

120

0

200

400

600

800

1000

1200

Ap

r-1

1

Au

g-1

1

Dec-1

1

Ap

r-1

2

Au

g-1

2

Dec-1

2

Ap

r-1

3

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-1

5

Au

g-1

5

Dec-1

5

Ap

r-1

6

Au

g-1

6

Dec-1

6

Ap

r-1

7

Au

g-1

7

Dec-1

7

(mn)

(Rs b

n)


0

50

100

150

200

250

300

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Ja

n-1

7

Fe

b-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Ju

n-1

7

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Ja

n-1

8

Fe

b-1

8

Ma

r-18

Ap

r-18



6











0

20

40

60

80

100

120

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Feb-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

Ap

r-18


0

100

200

300

400

500

600

700

800

900

1000

(Rs b

n)

Cards value at POS

0

100

200

300

400

500

600

700

(rs b

n)



0

500

1000

1500

2000

2500

3000

3500

4000

Ap

r-16

May-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Ma

r-17

Ap

r-17

May-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

(Rs)



7

















0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8



8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight











do it







knowrdquo















product of laziness















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight























Leverage












a hidden cost














and admired

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






















retirement
















change








your teens and 20s

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








canrsquot fathom




















and values














Harshal
Highlight
Harshal
Highlight














think






prophets

































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




























directly own stocks



nearly as urgent




















terms

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


































potential
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
















be wrong













people

























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight





and reason









error











wealth















moneyrdquo








stuff



Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




it in a cast












action is to fix it




















coming true
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








lives




















and different goals
























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






Which is dangerous










ruinrdquo
























succeed








it matters

Harshal
Highlight
Harshal
Highlight

















world should work

















Harshal
Highlight
Harshal
Highlight





























your future












Harshal
Highlight























again




with the punches






FEATURED




larr PREV NEXTrarr

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


2










0

5

10

15

20

25

Jan

-05

Jul-0

5

Jan

-06

Jul-0

6

Jan

-07

Jul-0

7

Jan

-08

Jul-0

8

Jan

-09

Jul-0

9

Jan

-10

Jul-1

0

Jan

-11

Jul-1

1

Jan

-12

Jul-1

2

Jan

-13

Jul-1

3

Jan

-14

Jul-1

4

Jan

-15

Jul-1

5

Jan

-16

Jul-1

6

Jan

-17

Jul-1

7

Jan

-18

(Rs tn

)


116

4

6

8

10

12

14

Jan

11

May 1

1

Se

p 1

1

Jan

12

Ma

y 1

2

Se

p 1

2

Jan

13

Ma

y 1

3

Se

p 1

3

Jan

14

Ma

y 1

4

Se

p 1

4

Jan

15

Ma

y 1

5

Se

p 1

5

Jan

16

Ma

y 1

6

Se

p 1

6

Jan

17

Ma

y 1

7

Se

p 1

7

Jan

18

Ma

y 1

8

CIC as a of GDP


3











00

05

10

15

20

25

30

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Ju

l12

Oct1

2

Jan

13

Ap

r1

3

Ju

l13

Oct1

3

Jan

14

Ap

r1

4

Ju

l14

Oct1

4

Jan

15

Ap

r1

5

Ju

l15

Oct1

5

Jan

16

Ap

r1

6

Ju

l16

Oct1

6

Jan

17

Ap

r1

7

Ju

l17

Oct1

7

Jan

18

(Rs trn

)


0

100

200

300

400

500

600

700

800

900

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Jul1

2

Oct1

2

Jan

13

Ap

r1

3

Jul1

3

Oct1

3

Jan

14

Ap

r1

4

Jul1

4

Oct1

4

Jan

15

Ap

r1

5

Jul1

5

Oct1

5

Jan

16

Ap

r1

6

Jul1

6

Oct1

6

Jan

17

Ap

r1

7

Jul1

7

Oct1

7

Jan

18



4






irreversible trend


Mode of Transaction




Paper Clearing 367 298 -19 22343 21308 -5


- NEFT 499 548 10 38527 52759 37

- IMPS 190 309 63 1538 2803 82




- Debit Card at POS 852 902 6 1205 1200 0



UPI 14 501 34x 60 589 89x





Mobile Banking 315 676 114 4394 3649 -17










0

5

10

15

20

25

30

35

40

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

Ma

y1

3

Oct1

3

Ma

r14

Au

g1

4

Jan

15

Jun

15

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7

(Rs tn)


55

0

200

400

600

800

1000

1200

1400

1600

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

May1

3

Oct1

3

Ma

r14

Au

g1

4

Ja

n1

5

Ju

n1

5

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7


72


5










0

50

100

150

200

250

0

5

10

15

20

25

Ap

r-11

Au

g-1

1

Dec-1

1

Ap

r-12

Au

g-1

2

Dec-1

2

Ap

r-13

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-15

Au

g-1

5

Dec-1

5

Ap

r-16

Au

g-1

6

Dec-1

6

Ap

r-17

Au

g-1

7

Dec-1

7

(mn)

(Rs tn)


0

20

40

60

80

100

120

0

200

400

600

800

1000

1200

Ap

r-1

1

Au

g-1

1

Dec-1

1

Ap

r-1

2

Au

g-1

2

Dec-1

2

Ap

r-1

3

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-1

5

Au

g-1

5

Dec-1

5

Ap

r-1

6

Au

g-1

6

Dec-1

6

Ap

r-1

7

Au

g-1

7

Dec-1

7

(mn)

(Rs b

n)


0

50

100

150

200

250

300

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Ja

n-1

7

Fe

b-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Ju

n-1

7

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Ja

n-1

8

Fe

b-1

8

Ma

r-18

Ap

r-18



6











0

20

40

60

80

100

120

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Feb-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

Ap

r-18


0

100

200

300

400

500

600

700

800

900

1000

(Rs b

n)

Cards value at POS

0

100

200

300

400

500

600

700

(rs b

n)



0

500

1000

1500

2000

2500

3000

3500

4000

Ap

r-16

May-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Ma

r-17

Ap

r-17

May-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

(Rs)



7

















0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8



8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
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do it







knowrdquo















product of laziness















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Leverage












a hidden cost














and admired

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retirement
















change








your teens and 20s

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canrsquot fathom




















and values














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think






prophets

































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directly own stocks



nearly as urgent




















terms

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potential
















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people

























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error











wealth















moneyrdquo








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it in a cast












action is to fix it




















coming true
















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lives




















and different goals
























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3











00

05

10

15

20

25

30

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Ju

l12

Oct1

2

Jan

13

Ap

r1

3

Ju

l13

Oct1

3

Jan

14

Ap

r1

4

Ju

l14

Oct1

4

Jan

15

Ap

r1

5

Ju

l15

Oct1

5

Jan

16

Ap

r1

6

Ju

l16

Oct1

6

Jan

17

Ap

r1

7

Ju

l17

Oct1

7

Jan

18

(Rs trn

)


0

100

200

300

400

500

600

700

800

900

Ap

r1

1

Jul1

1

Oct1

1

Jan

12

Ap

r1

2

Jul1

2

Oct1

2

Jan

13

Ap

r1

3

Jul1

3

Oct1

3

Jan

14

Ap

r1

4

Jul1

4

Oct1

4

Jan

15

Ap

r1

5

Jul1

5

Oct1

5

Jan

16

Ap

r1

6

Jul1

6

Oct1

6

Jan

17

Ap

r1

7

Jul1

7

Oct1

7

Jan

18



4






irreversible trend


Mode of Transaction




Paper Clearing 367 298 -19 22343 21308 -5


- NEFT 499 548 10 38527 52759 37

- IMPS 190 309 63 1538 2803 82




- Debit Card at POS 852 902 6 1205 1200 0



UPI 14 501 34x 60 589 89x





Mobile Banking 315 676 114 4394 3649 -17










0

5

10

15

20

25

30

35

40

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

Ma

y1

3

Oct1

3

Ma

r14

Au

g1

4

Jan

15

Jun

15

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7

(Rs tn)


55

0

200

400

600

800

1000

1200

1400

1600

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

May1

3

Oct1

3

Ma

r14

Au

g1

4

Ja

n1

5

Ju

n1

5

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7


72


5










0

50

100

150

200

250

0

5

10

15

20

25

Ap

r-11

Au

g-1

1

Dec-1

1

Ap

r-12

Au

g-1

2

Dec-1

2

Ap

r-13

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-15

Au

g-1

5

Dec-1

5

Ap

r-16

Au

g-1

6

Dec-1

6

Ap

r-17

Au

g-1

7

Dec-1

7

(mn)

(Rs tn)


0

20

40

60

80

100

120

0

200

400

600

800

1000

1200

Ap

r-1

1

Au

g-1

1

Dec-1

1

Ap

r-1

2

Au

g-1

2

Dec-1

2

Ap

r-1

3

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-1

5

Au

g-1

5

Dec-1

5

Ap

r-1

6

Au

g-1

6

Dec-1

6

Ap

r-1

7

Au

g-1

7

Dec-1

7

(mn)

(Rs b

n)


0

50

100

150

200

250

300

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Ja

n-1

7

Fe

b-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Ju

n-1

7

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Ja

n-1

8

Fe

b-1

8

Ma

r-18

Ap

r-18



6











0

20

40

60

80

100

120

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Feb-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

Ap

r-18


0

100

200

300

400

500

600

700

800

900

1000

(Rs b

n)

Cards value at POS

0

100

200

300

400

500

600

700

(rs b

n)



0

500

1000

1500

2000

2500

3000

3500

4000

Ap

r-16

May-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Ma

r-17

Ap

r-17

May-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

(Rs)



7

















0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8



8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for






GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight











do it







knowrdquo















product of laziness















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight























Leverage












a hidden cost














and admired

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






















retirement
















change








your teens and 20s

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








canrsquot fathom




















and values














Harshal
Highlight
Harshal
Highlight














think






prophets

































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




























directly own stocks



nearly as urgent




















terms

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


































potential
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
















be wrong













people

























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight





and reason









error











wealth















moneyrdquo








stuff



Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




it in a cast












action is to fix it




















coming true
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








lives




















and different goals
























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






Which is dangerous










ruinrdquo
























succeed








it matters

Harshal
Highlight
Harshal
Highlight

















world should work

















Harshal
Highlight
Harshal
Highlight





























your future












Harshal
Highlight























again




with the punches






FEATURED




larr PREV NEXTrarr

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


4






irreversible trend


Mode of Transaction




Paper Clearing 367 298 -19 22343 21308 -5


- NEFT 499 548 10 38527 52759 37

- IMPS 190 309 63 1538 2803 82




- Debit Card at POS 852 902 6 1205 1200 0



UPI 14 501 34x 60 589 89x





Mobile Banking 315 676 114 4394 3649 -17










0

5

10

15

20

25

30

35

40

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

Ma

y1

3

Oct1

3

Ma

r14

Au

g1

4

Jan

15

Jun

15

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7

(Rs tn)


55

0

200

400

600

800

1000

1200

1400

1600

Ap

r1

1

Se

p1

1

Fe

b1

2

Jul1

2

Dec1

2

May1

3

Oct1

3

Ma

r14

Au

g1

4

Ja

n1

5

Ju

n1

5

Nov1

5

Ap

r1

6

Se

p1

6

Fe

b1

7

Jul1

7

Dec1

7


72


5










0

50

100

150

200

250

0

5

10

15

20

25

Ap

r-11

Au

g-1

1

Dec-1

1

Ap

r-12

Au

g-1

2

Dec-1

2

Ap

r-13

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-15

Au

g-1

5

Dec-1

5

Ap

r-16

Au

g-1

6

Dec-1

6

Ap

r-17

Au

g-1

7

Dec-1

7

(mn)

(Rs tn)


0

20

40

60

80

100

120

0

200

400

600

800

1000

1200

Ap

r-1

1

Au

g-1

1

Dec-1

1

Ap

r-1

2

Au

g-1

2

Dec-1

2

Ap

r-1

3

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-1

5

Au

g-1

5

Dec-1

5

Ap

r-1

6

Au

g-1

6

Dec-1

6

Ap

r-1

7

Au

g-1

7

Dec-1

7

(mn)

(Rs b

n)


0

50

100

150

200

250

300

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Ja

n-1

7

Fe

b-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Ju

n-1

7

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Ja

n-1

8

Fe

b-1

8

Ma

r-18

Ap

r-18



6











0

20

40

60

80

100

120

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Feb-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

Ap

r-18


0

100

200

300

400

500

600

700

800

900

1000

(Rs b

n)

Cards value at POS

0

100

200

300

400

500

600

700

(rs b

n)



0

500

1000

1500

2000

2500

3000

3500

4000

Ap

r-16

May-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Ma

r-17

Ap

r-17

May-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

(Rs)



7

















0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8



8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight











do it







knowrdquo















product of laziness















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight























Leverage












a hidden cost














and admired

Harshal
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Harshal
Highlight
Harshal
Highlight
Harshal
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Harshal
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Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






















retirement
















change








your teens and 20s

Harshal
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Harshal
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Harshal
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Harshal
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Harshal
Highlight








canrsquot fathom




















and values














Harshal
Highlight
Harshal
Highlight














think






prophets

































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




























directly own stocks



nearly as urgent




















terms

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


































potential
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
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Harshal
Highlight
















be wrong













people

























Harshal
Highlight
Harshal
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Harshal
Highlight





and reason









error











wealth















moneyrdquo








stuff



Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




it in a cast












action is to fix it




















coming true
















Harshal
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Harshal
Highlight
Harshal
Highlight








lives




















and different goals
























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






Which is dangerous










ruinrdquo
























succeed








it matters

Harshal
Highlight
Harshal
Highlight

















world should work

















Harshal
Highlight
Harshal
Highlight





























your future












Harshal
Highlight























again




with the punches






FEATURED




larr PREV NEXTrarr

Harshal
Highlight
Harshal
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Harshal
Highlight


5










0

50

100

150

200

250

0

5

10

15

20

25

Ap

r-11

Au

g-1

1

Dec-1

1

Ap

r-12

Au

g-1

2

Dec-1

2

Ap

r-13

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-15

Au

g-1

5

Dec-1

5

Ap

r-16

Au

g-1

6

Dec-1

6

Ap

r-17

Au

g-1

7

Dec-1

7

(mn)

(Rs tn)


0

20

40

60

80

100

120

0

200

400

600

800

1000

1200

Ap

r-1

1

Au

g-1

1

Dec-1

1

Ap

r-1

2

Au

g-1

2

Dec-1

2

Ap

r-1

3

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-1

5

Au

g-1

5

Dec-1

5

Ap

r-1

6

Au

g-1

6

Dec-1

6

Ap

r-1

7

Au

g-1

7

Dec-1

7

(mn)

(Rs b

n)


0

50

100

150

200

250

300

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Ja

n-1

7

Fe

b-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Ju

n-1

7

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Ja

n-1

8

Fe

b-1

8

Ma

r-18

Ap

r-18



6











0

20

40

60

80

100

120

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Feb-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

Ap

r-18


0

100

200

300

400

500

600

700

800

900

1000

(Rs b

n)

Cards value at POS

0

100

200

300

400

500

600

700

(rs b

n)



0

500

1000

1500

2000

2500

3000

3500

4000

Ap

r-16

May-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Ma

r-17

Ap

r-17

May-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

(Rs)



7

















0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8



8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































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6











0

20

40

60

80

100

120

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Feb-1

7

Ma

r-17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

Ap

r-18


0

100

200

300

400

500

600

700

800

900

1000

(Rs b

n)

Cards value at POS

0

100

200

300

400

500

600

700

(rs b

n)



0

500

1000

1500

2000

2500

3000

3500

4000

Ap

r-16

May-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Ma

r-17

Ap

r-17

May-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Ma

r-18

(Rs)



7

















0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8



8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail

























criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight











do it







knowrdquo















product of laziness















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight























Leverage












a hidden cost














and admired

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






















retirement
















change








your teens and 20s

Harshal
Highlight
Harshal
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Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








canrsquot fathom




















and values














Harshal
Highlight
Harshal
Highlight














think






prophets

































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




























directly own stocks



nearly as urgent




















terms

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


































potential
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
















be wrong













people

























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight





and reason









error











wealth















moneyrdquo








stuff



Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




it in a cast












action is to fix it




















coming true
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








lives




















and different goals
























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






Which is dangerous










ruinrdquo
























succeed








it matters

Harshal
Highlight
Harshal
Highlight

















world should work

















Harshal
Highlight
Harshal
Highlight





























your future












Harshal
Highlight























again




with the punches






FEATURED




larr PREV NEXTrarr

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


7

















0

20

40

60

80

100

120

140

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(Rs b

n)

Value m-Wallet

0

50

100

150

200

250

300

350

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Ja

n-1

5

Ju

n-1

5

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn)

Volume m-Wallet

150

155

160

165

170

175

180

185

190

195

200

500

1000

1500

2000

2500

3000

Ap

r-15

Jun

-15

Au

g-1

5

Oct-

15

Dec-1

5

Fe

b-1

6

Ap

r-16

Jun

-16

Au

g-1

6

Oct-

16

Dec-1

6

Fe

b-1

7

Ap

r-17

Jun

-17

Au

g-1

7

Oct-

17

Dec-1

7

Fe

b-1

8



8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016













16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight











do it







knowrdquo















product of laziness















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight























Leverage












a hidden cost














and admired

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






















retirement
















change








your teens and 20s

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








canrsquot fathom




















and values














Harshal
Highlight
Harshal
Highlight














think






prophets

































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




























directly own stocks



nearly as urgent




















terms

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


































potential
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
















be wrong













people

























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight





and reason









error











wealth















moneyrdquo








stuff



Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




it in a cast












action is to fix it




















coming true
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








lives




















and different goals
























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






Which is dangerous










ruinrdquo
























succeed








it matters

Harshal
Highlight
Harshal
Highlight

















world should work

















Harshal
Highlight
Harshal
Highlight





























your future












Harshal
Highlight























again




with the punches






FEATURED




larr PREV NEXTrarr

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


8






20

24

28

32

36

40

500

600

700

800

900

1000

Ap

r-16

Ma

y-1

6

Jun

-16

Jul-1

6

Au

g-1

6

Se

p-1

6

Oct-

16

Nov-1

6

Dec-1

6

Jan

-17

Fe

b-1

7

Mar-

17

Ap

r-17

Ma

y-1

7

Jun

-17

Jul-1

7

Au

g-1

7

Se

p-1

7

Oct-

17

Nov-1

7

Dec-1

7

Jan

-18

Fe

b-1

8

Mar-

18

(mn)

(mn)


0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Feb-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Feb-1

7

Jul-1

7

Dec-1

7

(mn

)


0

2

4

6

8

10

12

14

Ap

r-11

Se

p-1

1

Fe

b-1

2

Jul-1

2

Dec-1

2

Ma

y-1

3

Oct-

13

Ma

r-14

Au

g-1

4

Jan

-15

Jun

-15

Nov-1

5

Ap

r-16

Se

p-1

6

Fe

b-1

7

Jul-1

7

Dec-1

7

(Rs t



9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t





















76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018












Page 10




Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight











do it







knowrdquo















product of laziness















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight























Leverage












a hidden cost














and admired

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






















retirement
















change








your teens and 20s

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








canrsquot fathom




















and values














Harshal
Highlight
Harshal
Highlight














think






prophets

































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




























directly own stocks



nearly as urgent




















terms

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


































potential
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
















be wrong













people

























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight





and reason









error











wealth















moneyrdquo








stuff



Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




it in a cast












action is to fix it




















coming true
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








lives




















and different goals
























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






Which is dangerous










ruinrdquo
























succeed








it matters

Harshal
Highlight
Harshal
Highlight

















world should work

















Harshal
Highlight
Harshal
Highlight





























your future












Harshal
Highlight























again




with the punches






FEATURED




larr PREV NEXTrarr

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


9










0

10

20

30

40

50

60

70

80

90

100


Digital ATM+Branch

100

5448

0

20

40

60

80

100

120




10










Branches 43

ATM 40

Phone Banking

14


2008 Branches 8

ATM 6

Phone Banking

1


2018

-5

0

5

10

15

20

25

30

35

40

-200

0

200

400

600

800

1000

1200

1400

Housin

g

Ve

hic

le

Ed

ucation

Cre

dit C

ard

OS

Ad

v again

st

Fix

ed

Deposits

Cons D

ura

ble

s

Ad

v again

st

Share

B

onds O

thers

(Rs b

n)



11











0

20

40

60

80

100

120

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17



0

200

400

600

800

1000

1200

1400

1600

1800

Jan

-15

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

(Rs b

n)



0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

2000000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

Number of POS



12



0

5

10

15

20

25

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

10

20

30

40

50

60

70

80

Ap

r-1

1

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn)



0

50

100

150

200

250

300

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Jul-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




13



0

50

100

150

200

250

300

350

400

450

500

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Mar-

13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

20

40

60

80

100

120

140

160

Ap

r-11

Se

p-1

1

Mar-

12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Mar-

15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)

No of usage at POS


0

50

100

150

200

250

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Jul-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)




14




0

50

100

150

200

250

300

350

400

450

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8

(mn

)



0

200

400

600

800

1000

1200

Ap

r-11

Ju

l-1

1

Nov-1

1

Ma

r-12

Ju

l-1

2

Nov-1

2

Ma

r-13

Ju

l-1

3

Nov-1

3

Ma

r-14

Ju

l-1

4

Nov-1

4

Ma

r-15

Ju

l-1

5

Nov-1

5

Ma

r-16

Ju

l-1

6

Oct-

16

Fe

b-1

7

Jun

-17

Oct-

17

Fe

b-1

8

(Rs b

n)



0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

Ap

r-11

Se

p-1

1

Ma

r-12

Se

p-1

2

Ma

r-13

Se

p-1

3

Ma

r-14

Se

p-1

4

Ma

r-15

Se

p-1

5

Ma

r-16

Se

p-1

6

Fe

b-1

7

Au

g-1

7

Fe

b-1

8Number of ATMs



15



0

20

40

60

80

100

120

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7



0

1

2

3

4

5

6

7

8

9

10

Jan

-13

Jun

-13

Dec-1

3

Jun

-14

Dec-1

4

Jun

-15

Dec-1

5

Jun

-16

Dec-1

6

Jun

-17

Dec-1

7

(Rs tn)



Page 2

SPARK STRATEGY



SPARK STRATEGY

22 May 2018

BSE Sensex 34616

NSE Nifty 10516

Performance ()

1m 3m 12m

Sensex -21 02 108

BSE200 06 23 136






















years (Rs 505bn)











GAUTAM SINGH


+91 22 6176 6804



+91 44 4344 0022

ARJUN N

arjunsparkcapitalin

+91 44 4344 0081

RESEARCH ANALYSTS

-5

0

5

10

15

20

May

-17

Jun

-17

Jul-

17

Au

g-1

7Se

p-1

7O

ct-1

7N

ov-

17

De

c-1

7Ja

n-1

8Fe

b-1

8M

ar-1

8A

pr-

18

May

-18

Sensex BSE 200

Page 3









2 Sharp pick-up in

demand for Tractors



3 Two Wheelers

demand on the rise









7 Cement demand has

picked up but price




8 Muted demand for



Page 4




GDP size ($bn) 219 2577











SEZ (No) 12 222

Capital Lucknow -








2970 2965 2955 2825 2789 2470 2387

2214 2190

Sin

ga

po

re

Mal

ays

ia

Sou

th A

fric

a

Co

lom

bia

Pa

kist

an

Ch

ile

Fin

lan

d

Ba

ngl

ad

esh UP

GDP ($ bn)


USA China USA China

India Indonesia

1370 1282

323 261 224 208 193 186

0

200

400

600

800

1000

1200

1400

1600

China India United

States


Population (mn)



than Brazil

Page 5












27 26 25 23 22 21

18

10 10 9

6 6 5

1 1

-6 -7

UP

Ch

att

isg

arh

Ori

ssa

MP

Bih

ar

Ass

am

Jha

rkh

an

d

All

Sta

tes

De

lhi

Gu

jara

t

Ra

jast

ha

n

Ke

rala

WB

Pu

nja

b

Ma

ha

rash

tra

Ka

rna

tak

a

TN


23 22 20 19 17 16

15 14 11 11

8 7

4

-4

-8 -11

UP

Jha

rkh

an

d

Ori

ssa

Bih

ar

Ch

att

isg

arh

Gu

jara

t

WN

Ra

jast

ha

n

Pu

nja

b

Ass

am

Ke

rala

All

Sta

tes

Ta

mil

Na

du

De

lhi

Ma

ha

rash

tra

Ka

rna

tak

a


13 15

17

12

9

5

5

9 6

2

4

6

8

10

12

14

16

18





94

156

263

93

127

228

152 146 16

0

5

10

15

20

25

30

UP MP Gujarat


FY16 FY17 FY18

Page 6










controlling crimes





reach the doorstep

of the caller in

trou le


top to control not

only crime but to

strop any form of

extortion eve

teasi g et




cancelation







jail





Page 7





















criminal activities




35

80

91

00

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016



Page 8











16

39 56 57 63 56 63 64

85

131

169 188

220

-

50

100

150

200

250







85

55

33 28 27 27

21 20 17 14 10 5 1 0

-2 -9

-16

UP

Ch

att

isg

arh

Ra

jast

ha

n

Jha

rkh

an

d

Ori

ssa

MP

Pu

nja

b

All

Sta

tes

Ma

ha

rash

tra

Ass

am

WB

Ke

rala

Bih

ar

Ka

rna

tak

a

TN

De

lhi

Gu

jara

t















Page 9







76 76 81 92 95

103 106

107

59 65 72 76 82 87

93

106

22

15

11

17

14 16

13

2

0

5

10

15

20

25

0

20

40

60

80

100

120








a day power supply



electricity supply






5

10

18

12

18

22

0

5

10

15

20

25

2012 2015 2018















Source Census 2011

A














Top 5 Bottom 5






Page 11














1061

1960

1006

500

700

900

1100

1300

1500

1700

1900

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

FY

18

India UP (T+11Yrs)



1049

500

1000

1500

2000

2500

3000

3500




Maharashtra TN and


Agri 23

Industry 26

Services 51


belts









Page 12










hellip




585 532 481 465 430

415 468 519 535 570

1993-94 1999-00 2004-05 2009-10 2011-12


Food Non-food

111 121 38 62 50

70

198 214

21 19 100 83

481 430

2004-05 2011-12


Fuel amp light




Durable goods


medical

145 162

43 74 72 95

160

178 20

17 81

61

480 413

2011-12 2024-25E


Fuel amp light




Durable goods


325

749

1006

1900

0

200

400

600

800

1000

1200

1400

1600

1800

2000

FY0

5

FY0

6

FY0

7

FY0

8

FY0

9

FY1

0

FY1

1

FY1

2

FY1

3

FY1

4

FY1

5

FY1

6

FY1

7

FY1

8

FY1

9

FY2

0

FY2

1

FY2

2

FY2

3

FY2

4

FY2

5


Page 13



Power

Supply

Law and

order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Power

Supply

Law and

Order

Road

Infra

GDP

Growth

Income per

capita

Services

sector

Demography

Dependency on

Agriculture

Positive

Negative

Neutral


Page 14








bull Apparels shops









bull Pharmacy








emerging trends


Agra

Lucknow

Delhi

Shamli

Saharanpur

Meerut

Ghaziabad

Noida

Kanpur

Unnao

Barabanki

Etawah

Hathras

Page 30












in FY18RE


745 677 575 549 671

68 54

-150

40

224

-02

-02

-01

-01

00

01

01

02

02

03

-

100

200

300

400

500

600

700

800



300 299

295

298

291

286

288

290

292

294

296

298

300

302



53

450

295 298 296

00

10

20

30

40

50

60



93

81 86

82 76

0

1

2

3

4

5

6

7

8

9

10



Page 31


Fiscal deficit

Total

Expenditure

Market

Borrowings

Shortfall in

own tax

revenue

Fall in stamp

duty

Subsidies GDP

Rural

Spend

Pension

Capex vs

Revex

Urban Infra

Irrigation













estimates



estimates



















over FY18

Page 32





Key Highlights





during the year





















Agriculture 29 60 396 284 116 5547 3695 -592



Energy 482 340 177 181 278 -478 -468 537

Education 401 490 624 570 632 272 163 109

Public Works 45 237 192 195 222 -190 -178 138


Debt Repayment 176 203 220 220 305 84 84 388


Others 1406 217 225 225 278 36 37 236











































Manoj Bahety

+91 22 6623 3362


Nilesh Aiya

+91 22 4040 7575


Ankit Dangayach

+91 22 6620 3077


Raj Koradia

+91 22 6623 3422


June 4 2018

THE SHIFT


EDEL PULSE






















collection target


by





2017



936 930 951859 837

889 880 893

1035940

0

250

500

750

1000

1250

Au

g-1

7

Se

p-1

7

Oc

t-1

7

No

v-1

7

De

c-1

7

Jan

-18

Fe

b-1

8

Ma

r-1

8

Ap

r-1

8

Ma

y-1

8

(IN

R b

n)


897987

1201

0

300

600

900

1200

1500


May18)

FY19 avg

monthly asking

rate

(IN

R b

n)



The SHIFT













presence

810

925

1147

0

250

500

750

1000

1250


(0

00

s)


34

42

58

00

15

30

45

60

75


(IN

R b

n)

Tax collected



Pulse on the ground





system servers




























transact in cash


The SHIFT









About DGSTI





(DGCEI)















mobile checking of




vehicles have been


way bill norms











Invoice matching

Reverse charge

mechanism (RCM)


RFID











































































significant






Perspective

The Value Of




Rohit Chauhan












SIGN IN SUBSCRIBE





of investing



for me








belittle his tools



Durable success










cut-off point















shareholders

























destroyed) wealth



EVENTS

Search Here










technology









Capacity to suffer














Platform Business















space




line














change is low



cheap










fanatic








not make it

It is quite rare




such companies



companies

So why study



















at rohitchauhan







Name




Recommend





Bloomberg





















March 31(thousands)

Value as ofMarch 31

($millions)



ALSN+133


8899 $3476 0


BAMA+043




5960 $3112 12

CarMax Inc KMX+141



LBTYK+267




Apple Inc AAPL+180


1209 $2028 12


ST+213


3880 $2010 2




CHTR+032





BRKB+037



LBRDK-025


1596 $1368 -16


AXTA+119



SBAC+026


5 $0876 -3

Hexcel Corp HXL+089













Comment

BACK TO TOP

MarketWatch

Site IndexTopics

MM








corporate credit

May 8 5 PM GMT

M

4

M

















to improve









2017







porary crises



20

25

30

35

40

45

50

55

60

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast

Long-term avg = 35


Exhibit 4


3

4

5

6

7

8

9

10

2003 2005 2007 2009 2011 2013 2015 2017 2019


MS fcast


Exhibit 5


2017 2018E 2019E 2020-22


GLOBAL 37 31 39 43 24 38 45 34

G10 23 16 22 26 04 20 27 13

US 23 20 27 31 04 22 28 12EA 25 18 21 23 05 19 31 12Japan 17 05 13 16 03 15 20 11UK 18 06 12 17 -01 10 18 14EM 48 42 50 56 37 50 58 48



M



growth in 1Q18






















































Exhibit 6


-2

-1

0

1

2

3

4

5

-4

-2

0

2

4

6

8

1995 1998 2001 2004 2007 2010 2013 2016 2019




Exhibit 7


-25

-15

-05

05

15

25

2002 2004 2007 2009 2012 2014 2017 2019

EMXC

DM

China


MS fcast


M

6













Exhibit 8


-5

-3

-1

1

3

5

7

9




G3














Exhibit 9


2012-16 2017-Now



bull Risk-averse



ised

Aggregate Demand



back


tions weak capex



Risks



recession


tion


bility risks



where





36Y in 2017 to 41Y in 2018 and 42Y in 2019

Exhibit 10


-01 -07

06 05

43

29 22 20

10

12 13 14

26

32 27 27

78

66 69 66

-1

0

1

2

3

4

5

6

7

8

9

2013 2016 2017 2018E



Real GDP Growth











tightening

M


M





















cators





March 2018)

















Exhibit 11


28

-4

-3

-2

-1

0

1

2

3

4

5



2013 Taper

Tantrum


Exhibit 12


0

1

2

3

4

5

6

7

8

9

10

-45

-40

-35

-30

-25

-20

-15

-10




2013 Taper

Tantrum










M

8















pressures in check

























Exhibit 13


-2

-1

0

1

2

3

4


US Core PCE

Euro Area Core


MS fcast


Exhibit 14


2017 2018E 2019E 2020-22


GLOBAL 25 28 29 31 24 28 32 28

G10 18 19 21 24 08 17 26 19

US 21 26 26 30 11 19 30 20

EA 15 15 17 18 04 16 21 17

Japan 05 07 11 13 03 10 17 15

UK 27 21 25 30 19 21 30 22

EM 31 35 34 35 35 35 36 34

China 16 21 24 26 19 25 28 25

India 33 50 46 44 55 44 43 40

Brazil 35 35 31 28 45 39 37 40

Russia 37 50 30 20 70 42 28 40


Exhibit 15


1

2

3

4

5

6

7

8






M


M


























labour markets


normalisation












Exhibit 17


Central Bank

Policy Action





1Q19



rate caps





Exhibit 16


2005-07

-1

0

1

2

3

4

-6

-4

-2

1

3

5

7

9




US Core PCE Y - RS



Dec-07
















M


M

Bear Base Bull




































limited toolkit



















sation by the BoJ














UK Jacob Nell





forecast horizon













M

18

M

Bear Base Bull










wage growth
















comfort zone

















growth cycle

















inflation








at 15 of GDP





































bear case


M


M























on growth


(852) 2239 7826

Avni Jain

(91) 6118 1850









year





























2016 2017 2018E 2019E

Real GDP (Y) 79 64 75 77









CPI (Y) 50 33 46 44

Core CPI (Y) 48 46 52 46

Policy rate (eop ) 625 600 625 675







L

(PDF version here)









money































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight











do it







knowrdquo















product of laziness















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight























Leverage












a hidden cost














and admired

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






















retirement
















change








your teens and 20s

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








canrsquot fathom




















and values














Harshal
Highlight
Harshal
Highlight














think






prophets

































Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




























directly own stocks



nearly as urgent




















terms

Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight


































potential
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
















be wrong













people

























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight





and reason









error











wealth















moneyrdquo








stuff



Harshal
Highlight
Harshal
Highlight
Harshal
Highlight
Harshal
Highlight




it in a cast












action is to fix it




















coming true
















Harshal
Highlight
Harshal
Highlight
Harshal
Highlight








lives




















and different goals
























Harshal
Highlight
Harshal
Highlight
Harshal
Highlight






Which is dangerous










ruinrdquo
























succeed








it matters

Harshal
Highlight
Harshal
Highlight

















world should work

















Harshal
Highlight
Harshal
Highlight





























your future












Harshal
Highlight























again




with the punches






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What we are reading Volume 2 - blog.abakkusinvest.com

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Transcript of What we are reading Volume 2 - blog.abakkusinvest.com