QE seignorage.pdf

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Global Asset Allocation12 October 2012

Flows & LiquidityQE's seignorage benefit

Global Asset Allocation

Nikolaos PanigirtzoglouAC

(44-20) 7134-7815

[email protected]

J.P. Morgan Securities plc

Seamus Mac Gorain

(44-20) 7134-7761

[email protected]


Matthew Lehmann

(44-20) 7134-7813

[email protected]


Leo Evans

(44-20) 7742-2537

[email protected]


Jigar Vakharia

(91-22) 6157-3281

[email protected]

J.P. Morgan India Private Limited

See page 13 for analyst certification and important disclosures.

The giant carry trade that G4 central banks are engaged in via QE and

repo operations is currently producing a seignorage profit of around$140bn per year.

The Fed is returning $80bn to the Treasury every year. The BoE has so

far accumulated coupons of 28bn in its APF Company and is

currently adding 14bn of coupons every year, or 1% of UK GDP.

QE shortens the liabilities of the consolidated public sector by replacing

government bond liabilities with overnight central bank reserveliabilities.

And this is where the cost of QE lies. When the interest on excess

reserves rises in the future, above 2.5% or so, the QE trade will becomea negative carry trade for the Fed or the BoE.

A downgrade of Spain to junk by Moodys only, would mechanicallygenerate very little forced selling by bond funds, likely around 400mn.

Around 260bn of European government securities are trading atnegative yields, down from over 700bn in July.

EMs share of global debt securities markets continues to rise but

remains low compared to EMs share of global GDP.

We have discussed the impact of QE in the past (e.g.F&L, Jun 22), focusing on2 main channels: 1) the price channel i.e. QE not only lowers real government

bond yields but also induces investors to shift to other asset classes with more

attractive yields relative to government bonds; 2) the quantity channel: QE

increases the capacity of debt capital markets by bolstering issuance in substituteasset classes such as HG corporate and hard currency EM bonds.

But one QE related flow which is often overlooked is the profit that central

banks make as a result of QE or more broadly as a result of the expansion of

their balance sheets. This profit is called seignorage and is effectively the

carry that central banks receive by buying securities or making loans such as

repos. These central bank assets are funded via the creation of central bank

reserves on which central banks pay a zero or close to a zero rate. The ECB

currently pays a zero rate on its excess reserves, the BoJ pays 10bp, the Fed pays25bp and the BoE pays 50bp. The yield on the assets they buy starts from 75bp

for the ECBs refinancing operations and the BoEs Funding for Lending

Scheme to 2% for US MBS, 3% for long-dated Gilts and 5% for peripheralbonds. .


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Nikolaos Panigirtzoglou(44-20) [email protected]

Indeed these seignorage profits are shown in the annual accounts of central

banks. The Fed made a profit of more than $80bn in net interest income in

2011 on a balance sheet of almost $3tr, i.e. a yield of 2.7%. The BoJ made a

profit of more than $8bn in net interest income in 2011 on a balance sheet of

$1.8tr, i.e. a yield of 45bp. The BoE accumulated coupons of more than $14bn

during 2011 alone in its Asset Purchase Facility on a (APF) balance sheet of

$530bn, a yield of 2.6%. The ECB does not produce annual accounts for the

Eurosystem as a whole but based on a current stock of $1.5tr of repo

operations with a yield of 75bp and $780bn of securities with an assumed yield

of 3%, we estimate that the Eurosystem makes a profit of close to $34bn a

year.

In total, the giant carry trade that G4 central banks are engaged in via

QE and repo operations is currently producing a profit of around $140bn

per year. This number is likely to increase by between 10%-20% as we

anticipate that G-4 central banks will add close to $1tr of bonds over the next

year, assuming (i) $480bn of MBS purchases from the Fed; (ii) some 15tr of

short-dated JGB purchases from the Bank of Japans Asset Purchase Facility;

(iii) a further 50bn of gilt purchases from the Bank of England, beyond whathas already been announced; and (iv) say, 100bn of OMT bond purchases by

the ECB.

The Fed, the BoJ and the Eurosystem return most of these seignorage profits to

their respective Treasuries. The Bank of England does not return its profits via

its QE portfolio to the Treasury but accumulates the coupons from its Gilt

purchases in the form of cash holdings of the APF company. The Companys

operations are fully indemnified by HMTreasury and in return any surplus

from these operations after the deduction of fees, operating costs and any tax

payable are due to HM Treasury. That is, the BoE does not immediately

return these profits to the government but these profits are nevertheless due to

the Treasury.

We estimate that so far 28bn of coupons have been accumulated which are

due to HMs Treasury. This 28bn represents 1.8% of GDP and compares to

annual government debt servicing costs of around 2.6% of GDP. It is also half

of the fiscal thrust, i.e. change in cyclically-adjusted primary balance, that

the UK is expected to apply between this year and 2015.

Looking at the US, seignorage profits are comparable. The $80bn per year that

the Fed returns to the US Treasury represents 0.5% of GDP or 20% of the

annual interest costs on government debt.

It is sometimes stated that QE cancels government debt in the sense that the

consolidated public sector that includes both the government and the central

bank has its total debt reduced by the amount of QE purchases. This is

incorrect, in our view. QE does not cancel public sector debt. QE simplyshortens the liabilities of the consolidated public sectorby replacing long-

term government bond liabilities with overnight central bank reserve liabilities.

In theory, the government could have achieved the same shortening in the

maturity of its liabilities by deciding to issue a lot more of Tbills instead of

government bonds, but obviously it would a take a lot longer.

It is true however that QE provides interest relief to the government and it

indeed becomes equivalent to government debt cancellation, but only for as

long as the interest the central bank pays on reserves is close to zero. But these

reserves, which are central bank liabilities, do not disappear from the system

and the central bank might need to pay a higher interest on these reserves in


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the future when monetary policy is normalized.

And this is where the cost of QE lies. If inflation becomes a problem in the

future, the central bank might need to raise its policy rate sharply increasing

the cost for the central bank in terms of servicing its reserve liabilities. If the

interest on reserves rises sufficiently, the central bank might face negativecarry on its bond holdings.

What is the threshold for the interest on excess reserves for the QE trade to

become a negative carry trade? We estimate that this threshold is around 3%

for the BoEs APF and around 2.5% for the Feds UST holdings. So it will

take some time before a rise in the interest on excess reserves starts generating

losses in the form of negative carry for the BoE or the Fed. The negative carry

problem is not relevant for refinancing operations such as those conducted by

the ECB or the BoE, as these operations are always conducted at a spread over

the policy rate.

But the negative carry issue changes the incentives for how central banks exit

their currently ultra-accommodative policy in the future, i.e. whether they

choose to raise the interest on excess reserves or to shrink their balance sheetby reducing the stock of their bond holdings.

In fact these two policy actions are distinct. All major G4 central banks have

introduced paying interest rate on reserves which they use as the effective

policy instrument. The interest on excess reserves serves as a floor for short-

term market interest rates as lenders will never lend their overnight funds at a

rate below the one they receive at central banks deposit facility. The last

major central bank to introduce paying interest on excess reserves was the BoJ

in November 2008, a month after the Fed started paying interest on excess

reserves

This means that central banks can tighten policy i.e. raise interest rates without

the need to reduce reserves or deposits. In other words the interest on excessreserves can serve as the effective policy instrument in a world of large excess

reserves. The ECB rate hikes in the spring of 2011 are a good example of how

central banks can tighten monetary policy in a world of large excess reserves

or deposits.

One technical issue arises when the market for overnight funds includes

institutions that do not earn interest on central bank deposits. This is the case

in the US (with agencies) and the UK. But even in these cases where the

federal funds rate or the SONIA rate traded below the interest paid on excess

reserves, the deviations were rather contained. And central banks can always

expand the number of financial institutions which earn interest on central bank

deposits to prevent market overnight rates falling below the interest on excess

reserves.

All this means, we believe, that when the need for policy tightening arises, this

policy tightening does not need to begin with a rise in short rates, which in turn

is going to bring the central bank more quickly to the negative carry position.

Policy tightening can also begin via rises in long-term interest rates. And most

likely, such a rise in long rates does not even require Large Scale Asset Sales

by central banks. In fact, the mere announcement by central banks that the

stock of their securities holdings will be allowed to roll off over time is likely

to cause a sharp rise in long-term interest rates. Such a rise in long-term rates

reduces both the speed and the amount of short interest rate increases needed

to apply enough tightening in the economy. In turn this should delay the time


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at which the central bank starts suffering from negative carry i.e. the time

at which the interest paid on reserves rises above the locked-in yield on its

bond holdings.

In fact, such a sequence, allowing long-term market interest rates to rise first

before the policy rate is increased, is not only motivated by P&Lconsiderations. It seems logical if one thinks about how central banks eased

policy in the first place. Short term rates were lowered first and when the

policy rate hit the zero bound, central banks engaged in QE to lower long rates.

A reversal of this sequence would imply a rise in long rates first, i.e. a

steepening of the yield curve first, followed by a rise in the policy rate.

What about potential markingto-market or capital losses from QE? Marking-

to-market is not relevant if the securities are kept to maturity. The BoEs APF

says: The majority of the Companys holdings of securities are gilts, which

are liabilities of the broader public sector. So the impact on the public sector

as a whole of any change in the market value of the gilts held by the Company

is matched by changes in the market value of those gilts on the liability side of

the public sector balance sheet.

Admittedly, the public sector might face capital losses if central banks decide

actively to sell their securities before they mature at a lower price than they

bought. From a P&L perspective alone, there is little incentive to do so

especially if, as we mentioned above, long rates rise significantly by the mere

announcement that the stock of bond holdings will be let to roll off. And this

rolling off process can reduce QE holdings relative quickly at least in the case

of the Fed. The Fed currently owns $1.7tr of UST and Agency securities

2/3rds of which matures by 2020. The Fed also owns $835bn of Agency MBS

securities which is currently paying down at a rate of $330bn a year. The

maturity schedule is slower in the case of the BoE, where 46% of the current

Gilt stock matures by 2020.

But if central banks had to actively sell a portion of their security holdings, bythe time they decide to do this they will have accumulated a cushion from

accumulated coupons and/or unrealized capital gains. For example, the BoEs

APF Company has already accumulated coupons of 28bn and unrealized

capital gains of 25bn. So they could theoretically withstand a 150bp rise in

the yield of their total stock of Gilts or 300bp if 50% of the stock had to be

sold today. But of course this cushion rises over time by the amount of

coupons central banks accumulate each year. The BoE looks set to accumulate

close to 14bn of coupons every year assuming a weighted average coupon of

4.4% currently. This means that by 2015 for example, the total coupon cushion

that the BoE will have accumulated would be 70bn on top of unrealized

capital gains of 25bn. In other words, if the BoE had to start raising interest

rates in 2016, they could theoretically withstand a 270bp rise in the market

yield of their total stock of Gilts or 540bp if 50% of the stock had to be sold.

But again central banks have a choice and they do not need to actively sell a

big part of their bond holdings, risking capital losses in the future. The P&L

considerations described above favour an unwinding of QE holdings

predominantly via a passive rolling off process. But whether these P&L

considerations will have a significant influence on how central banks exit their

accommodative policy and unwind their bond holdings eventually, remains to

be seen. Our economist Malcolm Barr reminds us that BOE policy makers

have already signaled that they will actively sell at least a portion of their Gilt

holdings as part of their exit process.


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GBI EMU would generate 370m of forced selling if Spainis downgraded to junk by Moodys only

S&Ps decision to downgrade Spain to BBB-, from BBB+, with negative

outlook came as markets anxiously await the outcome of Moodys downgrade

review, expected some time this month. Whilst S&Ps rating doesnt carry asmuch significance (at current levels) as either Moodys (to high-yield) or

DBRSs (ECB haircuts), this weeks events have reignited questions about

selling flows from benchmarked managers should Moodys decide to cut.

Across major IG sovereign bond indices, JPMs GBI EMU has the most

stringent ratings thresholds. For instance, to be excluded from the EMU

IG index JPM requires 1 of 3 ratings to be below IG, Barclays Capital

requires 2 of 3 to be below IG, Citigroup requires both Moodys and S&P to

be below IG and iBoxx uses an average rating methodology across all three.

Therefore, the most immediate source of selling pressure on Spanish bond

yields if Moodys does downgrade would likely come from funds

benchmarked to JPMs bond indices.

Using Bloombergs fund search function, we find 306 funds specify their

primary benchmarks as either GBI Global, GBI broad, GBI EU, GBI EMU

and GBI EMU IG, i.e. are European sovereign bond funds benchmarked to a

JPM index. These funds account for 107bn of AUM, although this estimate

of the total AUM benchmarked to these indices is low, as many funds report a

maturity bucket sub-index, of which there are too many to search manually,

among other estimation issues. However only 3.7bn, i.e. 3.4%, is directly

benchmarked to GBI EMU IG, which is the only index that would generate

forced selling in the event of a Moodys downgrade and according to our index

teams, the weight of Spanish bonds in this index is10%, so the maximum

potential selling from it 370mn.

Spains weight in the other indices, i.e. GBI Global, GBI broad, GBI EU, GBI

EMU, ranges from 2.5% for the GBI Global up to 10% for GBI EMU, so if wecontinue to assume that in aggregate these funds are aligned with their

benchmarks, this suggests they hold around 6.2bn of Spanish bonds (Figure

1). Whilst Spain will remain in all of these indices if it is downgraded to high-

yield, many managers may be forced to sell anyway due to riders in their

mandates which stipulate they cannot invest in sub-investment grade debt.

Even is such riders are in place, they do not necessarily trigger via a Moodys

only downgrade to junk.

Tracking the negative yield universe

Investors must accept negative nominal interest rates, that is, pay money in

order to place cash, if central banks establish very low or negative unsecured

rates, and/or if there is strong demand for the safest collateral, pushing reporates and government yields significantly below unsecured interbank rates.

Both these factors have been to the fore this year, leading to an increased

incidence of negative nominal rates. Overnight rates in both Switzerland

and Denmark have been persistently negative, the former marginally and

intermittently for over a year, the latter only since June, but with rates getting

as low as negative 50bp. The persistence of negative market rates pressures

banks to pass them through to their depositors, with press reports this week

suggesting that a number of banks were charging investors for taking

DKK and CHF deposits, with one reportedly charging 75bp per annum for

taking CHF deposits. The Danish Bankers Association also said that its

Figure 1: Mutual fund AUM benchmarked to themajor JPM Government bond indicesbn

Source: Bloomberg, J.P.Morgan

Figure 2: Euro area government bonds and billstrading at negative interest ratesbn

Source: Bloomberg, J.P.Morgan

AUM % Spain AUM Spain

GBI Global 42.8 2.7 1.1

GBI Broad 9.0 2.5 0.2

GBI EU 19.5 8.3 1.6

GBI EMU 32.0 10.0 3.2

GBI EMU IG 3.7 10.4 0.4

Total 107.0 100 6.6

0

100

200

300400

500

600

700

800

Jan-12 Mar-12 M ay -12 Ju l-12 Sep-12


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members were considering whether to pass negative market rates on to

customers.

The ECB's deposit rate cut to zero in July brought euro unsecured rates to

around 10 basis points, and they appear set to remain around that level, with

the ECB now looking unlikely to move to a negative deposit rate.

The cut in the deposit facility rate has been followed by a small number of

trades at negative rates in the market for unsecured euro deposits in London

(EURONIA rather than the much larger EONIA market), likely triggered by

operational factors (e.g. cash payments late in the day for institutions without

access to the ECB's deposit facility), and perhaps stronger credit quality among

the much smaller EURONIA panel. But the magnitude of these trades is

limited, with around 16bn in cumulative volume at negative rates since July,

less than the daily volume in EONIA.

In repo markets, euro general collateral secured rates have been hovering just

above zero, with lenders of cash very reluctant to accept negative interest rates.

But with GC rates around zero that means that investors looking to cover short

positions in scarce collateral routinely have to lend cash at negative rates.

Negative nominal rates have been far more prevalent in short-dated

government bonds than in repo or unsecured markets.Figure 2 shows an

estimate of the amount of Euro area government bonds and bills trading at

negative yields over time. We use pricing data from our JPM bond indices for

bonds of over one year's maturity, and Bloomberg bid prices for bills and sub-

1yr bonds, while recognizing that there is greater uncertainty over the yield of

less-frequently-traded money market instruments.

On this estimate, around 190bn of Euro area government securities are

currently trading with negative nominal yields, almost all of them with

maturities of one year or lower, and almost all of them German government

bonds or bills. To this we can add CHF45bn of Swiss government securities,and DKK220bn of Danish government bonds, for a total of around 260bn of

European government bonds trading at negative yields.

Back in July, before the ECB's shift towards bond purchases, as much as

700bn of Euro area government securities were trading with negative

yields, of which almost half had more than one year to maturity, and 80% were

from Germany.

The climate of persistently low money market rates in the Euro area is likely to

keep money market funds under pressure, although they saw an inflow in

August, after two months of outflows. The pass-through to Euro area corporate

and retail deposit rates is less clear though. Despite recent improvements,

peripheral banks still remain under severe funding pressure, and even in the

core, banks have passed only around half the fall in money markets rates overthe past year on to depositors.

EM continues to grow as an asset class

Our colleagues in emerging markets strategy this week reported that the EM

corporate asset class reached the $1tr milestone (seeEMOS, Joyce Chang, 4

Oct). We take this opportunity to look at the whole of the emerging market

asset class and see where we stand.

In order to get a more complete picture of the size of the EM debt market, we

use data from the BIS on total debt securities outstanding as opposed to our

EM bond indices, which cover a much smaller universe of purely the tradable

Figure 3: EM vs. DM outstanding debt securitiesas a share of GDPShare of GDP. Includes external and local debt

securities issued by governments and corporates.

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

220%

Dec-94 Jun-98 Nov-01 May-05 Nov-08 May-12

DM

EM


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bonds. The BIS statistics include outstanding debt securities not eligible for

inclusion in our bond indices for a variety of tradability reasons.

According to these BIS data, the total EM debt security universe is currently

around $12tr. This includes external and local currency debt issued by both

sovereigns and corporates. This equates to around 45% of EM GDP, a stillvery small amount relative to GDP when compared to developed markets. DM

debt securities are currently in the region of $86tr, or almost 190% of GDP

(Figure 3).

Figure 4 shows EMs share of total debt and equity markets, which continues

to rise for debt but has stalled somewhat for equities. EM equities account for

16% of global equity market capitalization and EM debt securities account for

12% of total outstanding debt securities. But these EM equity and debt security

shares are still well below the EM share in global GDP, which stood at 35% in

2011.

Source: BIS, IMF and J.P.Morgan

Figure 4: EM share of global debt and equitymarketsShare of total global equity market cap and

outstanding debt securities. Equity market is proxiedby the Datastream global equity index. Total debt

outstanding is using BIS data.

Source: BIS, Datastream and J.P.Morgan

4%

6%

8%

10%

12%

14%

16%

18%

Dec-95 M ar-99 Jun-02 Sep-05 Nov-08 Feb-12

Debt

Equities


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Table A1: Weekly Flow Monitor

Based on 4-week averages. Gross bond issuance includes all corporates incl.financials. The diamond is the current observation. The thin blue line marks thedistance between the min and max for the complete time series. The thick bluebar shows the interquartile range. MF flows use Lipper data for the current

week and ICI for historical data. Current weeks observation is in column on theright. ETF flows are from Bloomberg. (in $bns).

Source: Bloomberg, ICI, Lipper, Dealogic, Reuters, Federal Reserve, ECB, J.P. Morgan

Table A2: Monthly Trading Volume Monitor

Based on YoY changes. USTs are primary dealer transactions in all USgovernment securities. JGBs are OTC volumes in all Japanese governmentsecurities. Bunds, Gold, Oil and Copper are futures. Gold includes Gold ETFs.

The diamond is the current observation. The thin blue line marks the distancebetween the min and max for the complete time series. The thick blue barshows the interquartile range.

Source: Bloomberg, FE Reserve, Trace, Japan Securities Dealer Association, WFE, J.P. Morgan.

* Data with one month lag.

Chart A1: Weekly Spec Position Monitor

Net spec positions are the number of long contracts minus the number of shortusing CFTC futures only data. This net position is then converted to a USDamount by multiplying by the contract size and then the corresponding futuresprice. To proxy for speculative investors, commodity positions use the managed

money category, while the other assets use the non-commercial category. Thechart shows the z-score of t hese net positions, i.e. the current net positionminus the average over the whole sample divided by the standard deviation ofthe weekly positions over the whole sample. US rates is a duration-weightedcomposite of the individual UST series plus the Eurodollar contract. The samplestarts on the 13th of June 2006.

Source: Bloomberg, CFTC, J.P. Morgan

Chart A2: Equity vs. UST positions

Equity positions include the S&P500, Dow Jones, Nasdaq and the Nikkei. The

UST series is a duration weighted aggregate of the Eurodollar, UST2YR,

UST5YR, UST10YR, UST long bond and the UST Ultra long bond futures.

Source: Bloomberg, CFTC J.P. Morgan

MF & ETF Flows(4wk av gs) MIN MAX 10-Oct

All Equity 0.44

All Bond 3.24

US Equity -1.24

Intl. Equity 1.89

Taxable Bonds 3.18

Municipal Bonds 0.98

Equity Supply(YoY changes in rolling 4wk flows) 12-Oct

Global IPOs 0.84

Global Secondary Offerings 1.81

Gross bond issuance (YoY changes in rolling 4wk flows) 12-OctUS Bond Issuance 7.01

WE Bond Issuance 13.61

Corporate activity(YoY changes in rolling 4wk flows) 12-Oct

Global M&A 28.11

US buybacks 0.61

Non-US buy backs 1.03

Equities MIN MAX Sep-2012 (tr)

EM Equity $0.97

DM Equity $2.77

Govt Bonds

USTs $1.77

JGBs* 752

Bunds 2.51

Credit

US HG $0.24

US HY $0.11

US Convertibles $0.02

Commodities

Gold $0.64

Oil $0.77

Copper $0.20

-4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

VIX

BRL

USD

EUR

RUB

US Equities

CHF

US 5YR

Crude Oil

GBP

JPY

US 2YR

US 10YR

US T-Bonds

AUD

Copper

Gold

Corn

NZD

US Rates (incl. ED)

Wheat

MXN

CAD

Silver

25-Sep 12 02-Oct 12

Standard devations f rom mean weekly position

-600

-400

-200

0

200

400

600

-6

-4

-2

0

2

4

6

8

Nov-11 Jan-12 M ar-12 M ay -12 J ul-12 Sep-12

$bn $bn

Equity positions

UST positions

Last observation: 2-Oct-12


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Chart A3: Market health map

Each of the six axes corresponds to a key indicator for markets. The position

of the blue line on each axis shows how f ar the current observation is fromthe extremes at either end of the scale. The dotted line shows the same but

at the beginning of 2012 for comparison. For example, a reading at the

centre for value would mean that risky assets are the most expensive theyhave ever been while a reading at the other end of t he axis would mean they

are the cheapest they have ever been. See explanation on the right f or each

indicator. Overall, the larger the blue area within the hexagon, the better for

risky markets.

Explanation of indicators

All vari ables a re expr esse d as the perc ent ile of the dis tri but ion tha t t he

observation falls into. I.e. a reading in the middle of the axis means that the

observation falls exactly at the median of all historical observations.

Equity trading volumes: The YoY change in the average daily trading

volume of stocks on the NYSE.

Value: The slope of the risk-return tradeoff line calculated across USTs, US

HG and HY corporate bonds and US equities (see GMOS p. 6, Loeys et al,

Jul 6 2011 for more details).

Positions: The difference between flows into US domiciled equity and bond

funds. Chart at top left of page 9. We then smooth this using a Hodrick-

Prescott filter with a lambda parameter of 0.1. We then take the weekly

change in this smoothed series as shown in the fund flow indicator on page

9.

Flow momentum: The difference between flows into equity and HY credit

mutual funds (incl ETFs) and flows into bond f unds. Chart at top left of page

9. We then smooth this using a Hodrick-Prescott filter with a lambda

parameter of 0.1. We t hen take the weekly change in this smoothed series as

shown in the fund flow indicator on page 9.

Economic momentum: The 2-month change in the global manufacturingPMI. (See REVISITING: Using the Global PMI as trading signal, Nikolaos

Panigirtzoglou, Jan 2012).

Equity price momentum: The 6-month change in the S&P500 equity index.

Chart A4: Probability that the S&P500 rises over the next month

The probability is based on a probit regression of 3 variables, economic momentum, price momentum and positions on the S&P500 as described in the blue

box. The dotted line shows the average probability over the whole history of the time series since June 2006.

Source: Bloomberg, ICI, CFTC, Datastream, J.P. Morgan

To summarise the Market Health Map in one metric, we develop a regression model of the probability of the equity market

(the S&P500 index) rising over the next 4 weeks. In statistics, this regression model is called a probit model and it is a natural

way of summarising our Market Health Map given that the 6 signals are already expressed in percentile terms, i.e. the position

in each of the 6 axes reflects the percentile within the empirical probability distribution of each of the 6 signals. In this way, by

measuring the distance in probability rather than linear space we suppress the impact of outlier outcomes.

A model estimating the probability of a rise inthe S&P500 over the next month

P(S&P500t+4 > S&P500 t) = -0.04+ 1.29 x 2M change in the global PMIt (p-

value:0%)

+ 0.6 x 6M change in the S&P500 index t (p-

value:12%)

- 1.1 x positions t (p-value:0%)

Probit regression using weekly data. All explanatory

variables are expressed in percentile terms.

Source: J.P. Morgan

The regression uses only 3 signals out of the six in our Market

Health Map. Positions proxied by our risky vs. safe asset spec

position indicator (see Chart at top right of page 9), macro

momentum proxied by the 2-month change in the global PMI, and

price momentum proxied by the 6-month change in the S&P500

index. These three signals have the most significance in our

model for explaining whether equities go up or down over the

following 4-weeks. The remaining three signals in the Market

Health Map are less significant for the near term, so we exclude

them from the model.

Equity trading volumes

PositionsInversed

Flows

Economicmomentum

Equity pricemomentum

Value

600

800

1000

1200

1400

1600

1800

0%

20%

40%

60%

80%

100%

Jan-07 Oc t-07 Jul-08 Apr-09 Jan-10 Oct-10 Jul-11 Apr-12

S&P500

Probab ility that the S&P500 rallies over the next 4-weeks

12-Oct-12

S&P500

Last observation:


10/14

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12 October 2012


ETF Flow Radars (data as Oct 10th)

Flow Radars summarize total weekly ETF flows, as well as the relative movement across fund types. The charts are in percentile terms, such that for a

particular fund type, the center of the radar is the largest recorded weekly outflow (since 2005), and the outer-most point represents the largest inflow. The

position of the triangle on the axis give the historical ranking of last weeks flow. I.e. if the triangle crosses 66% of the way up the axis, only 33% of past flowswere larger and vice versa. The crosses on the axes give the zero flow points, i.e. crossing the axis above it represents an inflow and crossing the axis below

it represents an outflow.

Chart A5: Global Cross Asset Flow Radar Chart A6: US Bond Flow Radar

Source: J.P. Morgan. Bloomberg Source: J.P. Morgan. Bloomberg

Chart A7: Global Equity Flow Radar Chart A8: Mutual Fund Cash RadarFor US (Aug) and Euro area (July) domiciled funds. The centre of the radardenotes low cash positions relative to total assets over the past 2 years ofdata, i.e. UW c ash. The outer edge of each axis denotes cash OWs.

Source: J.P. Morgan. Bloomberg Source: J.P. Morgan, ECB, ICI

EquitiesMoney Markets

Bonds US HG

US HYMunis

US

EMDM ex US

US

Europe

Equity

BondHybrid


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Chart A9: Fund flow indicator

Difference between flows into Equity and Bond funds and ETFsThe thin blue line shows the 4-week average of this difference. The thickblack line shows a smoothed version of the same series. The smoothing isdone using a Hodrick-Prescott filter with a Lambda parameter of 0.1.

Source: Bloomberg, J.P. Morgan

Chart A11: Hedge fund monitor

Hedge fund equity exposureRolling 21-day beta of macro fund returns to returns on the S&P500. Thebeta represents the average exposure of macro hedge funds to equities overthe previous 21-days.

Source: Datastream, Bloomberg J.P. Morgan

Chart A10: Spec position indicator

Difference between net spec positions on risky and safe havenassetsWe calculate the net spec position in USD across 8 "risky" and 7 "safe"assets. These positions are then scaled by open interest and we take an

average of "risky" and "safe" assets to create two series. The chart is thensimply the difference between the "risky" and "safe" series. T he final seriesshown in the chart below is demeaned using data since 2006. The riskyassets are: Copper, GSCI, AUD, NZD, CAD, RUB, MXN and equities (anaggregate of the S&P500, Dow Jones, NASDAQ and Nikkei). The safeassets are: Gold, VIX, JPY, CHF, Silver, an aggregate of the UST andEurodollar futures and an aggregate USD index. The USD series is theinverse of the sum of positions in EUR, JPY, GBP, CHF, AUD, NZD, CAD,RUB and MXN futures. The UST series is a duration weighted aggregate ofthe Eurodollar, UST2YR, UST5YR, UST10YR, UST long bond and the USTUltra long bond futures.

Source: CFTC, J.P. Morgan

Chart A12: Option skew monitor

Skew is the difference between the implied volatility of out-of-the-money(OTM) call options and put options. A positive skew implies more demand

for calls than puts and a negative skew, higher demand for puts than calls. Itcan therefore be seen as an indicator of risk perception in that a highly

negative skew in equities is indicative of a bearish view. The chart below

shows a z-score of the skew, i.e. the skew minus a rolling two-year average

skew divided by a rolling two-year standard deviation of the skew. A positive

skew on iTraxx Main means investors favour buying protection, i.e. a short

risk position. A positive skew for the Bund reflects a long duration view, also

a short risk position.

Source: Bloomberg, J.P. Morgan

-20

-15

-10

-5

5

10

15

Feb-07 F eb-08 Feb-09 Feb-10 Feb-11 Feb-12

$bn per week

0


-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

Jan-10 Jun-10 Nov-10 Apr-11 Sep-11 Feb-12 Jul-12

10-Oct-12Last observation:

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12


-1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

German Bund

Crude

iTraxx Main

EURUSD

S&P500

11 -Oct- 201 2 0 5- Oct-2 01 2


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European Funding market monitor

Table A3: Bank deposits and ECB reliance

Deposits are non-seasonally adjusted Euro area non-bank, non-government deposits as of Aug 2012. We take total deposits (item 2.2.3. in MFI balancesheets minus deposits from other financial institutions, which includes deposits from securitized vehicles and financial holding corporations among others.

We also subtract repos (item 2.2.3.4) from the total figures to give a cleaner picture of deposits outside interbank borrowing. ECB borrowing and Target 2

balances are latest available. ECB borrowing is gross borrowing from regular MROs and LROs. ELA is Emergency Liquidity Assistance. The Chart shows theECB borrowing and Target 2 liability, i.e. the inverse of the Target 2 balance column in the table. The ECB borrowing in the chart is the same data as the ECB

borrowing column in the table.

Source: ECB, National Central Banks, J.P. Morgan Source: ECB, National Central Banks, J.P. Morgan

Chart A13: Euro area gross bank debt

issuance

Chart A14: US CP issued by non-US

financials

Includes secured, unsecured and securitized issuance in any currency.Excludes short-term debt (maturity less than 1-year) and self funded

issuance (where the issuing bank is the only book runner).

Commercial paper issued by non-US financial institutions in the US.

Source: Dealogic, J.P. Morgan Source: Federal Reserve

bn Target 2 balance ECB borrowing ELA Deposit 3m chng Deposit 12m chng

Austria -45 18 0.6% 4.7%

Belgium -29 40 1.5% 5.1%

Finland 70 4 0.9% 4.6%

France -4 176 1.8% 7.6%

Germany 695 77 1.9% 5.1%

Greece -108 30 101 -2.7% -18.6%

Ireland -111 79 40 -2.5% 2.6%

Italy -281 277 0.0% 1.8%

Luxembourg 113 5 0.8% -9.5%

Netherlands 125 28 1.2% 7.0%

Portugal -68 56 -0.4% 0.7%

Spain -400 383 -1.8% -6.5% -1000 -500 0 500

Germany

Netherlands

Luxembourg

Finland

France

Belgium

Austria

Portugal

Greece

Ireland

Italy

SpainGross total ECBborrowing

Target 2 liability(i.e. negativemeans asset)

bn

5

10

15

20

25

Jun-11 Jul-11 Sep-11 Nov-11 Jan-12 Mar-12 May-12 Jun-12 Aug-12

Periphery

Core

EMU bank unsecured gross issuance

bn


350

370

390

410

430

450

470

490

510

Jan- May- Sep- Jan- May- Sep-

$bn

10-Oct-12Last observation:


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Disclosures

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http://www.optionsclearing.com/publications/risks/riskstoc.pdfhttp://www.optionsclearing.com/publications/risks/riskstoc.pdfhttp://www.optionsclearing.com/publications/risks/riskstoc.pdf


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