CHAPTER 5 FINDINGS OF THE STUDY -...

352

CHAPTER 5

FINDINGS OF THE STUDY

The research mainly aimed at understanding;

i. Whether the selected indices confirm the existence of a certain anomaly?

ii. If anomalies exist, whether these anomalies are stable and consistent over time

and across indices considered i.e., are they true anomalies?

iii. Whether these anomalies observed, show any consistency with the existing

literature.

The major findings for each calendar anomaly observed from the econometric analysis

are summarized below:

5.1 Day-of-the-week effect results

The null hypothesis tested the absence of day-of-the-week seasonality in the BSE and

NSE indices. The day-of-the-week effect states that the daily average index returns in

the framework of an efficient market should be uniformly distributed over different days

of the week. The rejection of the null hypothesis points towards presence of a pattern in

the data and thus coefficients of the dummy variables are significantly different from

zero. The most often referred anomaly is the weekend effect, wherein the mean returns

observed on Monday should be significantly lower (negative) while the mean returns on

Friday has to be significantly higher (positive) in nature. The results of the econometric

analysis for all the indices are summarized in Table-181 to 183. These charts summarize

the significant weekdays considering standard OLS model, GARCH model, and

GARCH-M model respectively for sub-periods (pre- and post- 2002)1 and overall period

at one percent and five percent significance levels. The Table-181 provides the summary

of only key indices listed on BSE and NSE respectively namely BSE Sensex, CNX

Nifty and CNX Nifty Junior index. At first, considering the overall period, we notice

significant similarities in all three indices. The mean return is observed to be the highest

1 For the summary of the results, we considered two sub-periods for only those indices with data availability of minimum three years

before 2002.

353

on Wednesday consistently for NSE listed indices in all three models, whereas in case of

BSE Sensex, there seems to be no consistency (Woolridge (1991) and Lumsdaine and

Ng (1999))2 wherein Wednesday was observed to have the highest mean returns in

regression model, but, Friday and Monday were observed to have highest returns after

considering time varying volatility.3 The lowest return for all the three indices was

observed on Tuesday respectively4. Thus, Wednesday effect and Monday effect can be

considered to be weekdays of truly anomalous returns in the NSE indices and BSE

Sensex index respectively and thus Wednesday effect and Monday effect cannot be

explained by time varying volatility. Following Wang et.al (1997), the results of the sub-

period analysis points towards change in the stability of the day-of-the-week effect due

to structural changes which have taken place in the Indian capital markets during the

period, 1990 to 2011. In the sub-period I, it is observed that Wednesday being the

weekday with highest mean returns followed by Tuesday having the lowest returns in all

the indices considering the time varying market volatility. Whereas in sub-period II,

significantly higher returns on Friday and the lower returns on Tuesday are noticed, after

considering the time varying volatility for BSE Sensex and CNX Nifty Junior index5.

The Tables 182 and 183 present the results of day-of-the-week effect in returns and

volatility of BSE and NSE listed broader and sectoral indices. At first, considering the

broader indices mainly the mid-cap and small-cap indices for the overall period, we can

observe that Monday remains to be significant in all the three models except for NIFTY

Mid-cap50 index. Thus Monday effect can be considered as true anomaly. Monday and

Tuesday are observed to have the highest and the lowest returns for the overall period.

Only in case of NIFTY Mid-cap50 index, we can observe that Friday and Tuesday have

the highest and lowest returns respectively. Considering all the sectoral indices, Monday

appears to remain significant in all three models and hence can be depicted to be true

anomaly. In case of all sectoral indices except for S&P BSE TECK and NSE sectoral

indices, Monday mean returns are observed to be significantly higher when compared to

2 Infer that the previous results obtained on Indian capital markets are mainly based on failure of research papers to model the

conditional mean which inturn lead to erroneous conclusions. 3 The results deviate from the studies by Fields (1930), French(1980), Fama (1965) etc,. where they observed positive Friday returns

and negative Monday returns (weekend effect). 4 Jaffe and Westerfield (1985), Peiro (1994), Agarwal and Tandon (1994) point towards different patterns i.e., either Monday or

Tuesday having the least returns. 5 Lakonishok and Smidt (1988) and Agarwal & Tandon (1994), point towards disappearance of weekend effect gradually in many

countries.

354

other weekdays and Tuesday remains to have the lowest mean returns. Thus, the result

of the econometric models shows high positive returns on Wednesday and Monday for

broader indices and sectoral indices respectively. The largest mean returns on Monday

especially for sectoral indices (when compared to higher returns of Friday and lowest

returns on Monday as observed in developed countries) point towards lagging effect of

Indian sectors taking cues from the global markets. The results observed point towards

“wait and watch principle” followed by investors. These high returns towards the

beginning of the week followed by lowest returns on Tuesday is in contrast to the

evidence obtained from other markets. In case of broader indices especially BSE

Sensex, CNX Nifty and CNX Nifty junior index, higher significant returns are obtained

on Wednesday but with lowest returns on Tuesdays.6 Thus, a pattern of higher Mondays

and higher Wednesdays can be observed with intermittent lower Tuesdays. Thus,

investors can adopt buy- hold- sell strategy in case of broader indices and sell-hold-buy

strategy in case of sectoral indices to make abnormal gains. We also observed

previously that in case of Indian markets, the returns obtained seem to be particularly

higher in the first sub-period examined when compared to returns for the total time

period. The last sub-period examined in all the indices present lower returns which are

infact closer to those observed in developed countries.7 Moreover, the results indicate

that the Tuesday returns are significantly negative and have become still smaller in the

recent periods8. This trend of negative returns on Tuesday has also been noticed in other

markets too.9 Thus in trying to explain these findings for Indian stock market, it could

be argued that investors take a optimistic road in the beginning of the week taking cues

from international markets on Monday10

. Karmakar and Chakraborty (2003), Nath and

Dalvi (2004) , Selvarani and Jenefa (2009), Garg and Chhabra (2010) find presence of

day anomalies in the Indian stock market which in turn are high correlated with the

6 Deepa Mangala (2008), studied day-of-the-week effect on CNX Nifty index during the period 1991 to 2007. The study also found

highest positive returns on Wednesday and most negative returns on Tuesday for the entire period. 7 Bafna and Mathur (2010) find no significant presence of the day-of-the-week effect in BSE Sensex returns for the period 2000-

2010. 8 Deepa Mangala (2008), attribute the presence of high returns on Wednesday and lowest returns on Tuesday mainly to

introduction of rolling settlement (from Tuesday settlement) in NSE. 9 Jaffe and Westerfield (1985a), Condoyanni et al. (1987) observed negative returns on Tuesday in Singapore and France, While in

Australia and Japan, both Tuesday and Mondays were observed to have negative returns. 10

Lakonishok and Maberly (1990) believed weekend effect can be explained by participation of more retail investors in the market

during Monday when compared to institutional investors. Thus more trading by retail investors (especially selling) on Mondays may be the cause for weekend effect.

355

investment pattern of FIIs which also invest in the similar way. The studies also find the

day anomalies persistent in the recent years but slowly losing its consistency, thereby

reconfirming that various trading patterns adopted would not be profitable with time.

The studies also find net investments by FIIs to follow the pattern of Friday effect. After

confronting with the realities of Indian economy and understanding the performance of

sectoral indices, investors are observed to react in the broader index such as BSE

Sensex, CNX Nifty and CNX Nifty Junior which are nonetheless the combinations of

major sectors. Thus, the results indicate that investors can adopt varying trading

strategies dealing with sectoral indices and broader indices separately. The results

indicate that the day-of-the-week effect is persistent in Indian stock market and is

unique to Indian market. Thus, the findings reject the null hypothesis for presence of

day-of-the-week effect in Indian stock markets. In both broader and sectoral indices, the

anomalies appear to be stable in nature. But, the day-of-the-week effect seems to be

disappear with time as the margin of returns is observed to decline11

.

11

Bhattacharya, K., Sarkar, N. and Mukhopadhayay, D. (2008) obtained significant changes in returns and volatility since mid-

1990’s. They suggested possible interaction between banking sector and capital market could explain day-of-the-week effect in returns and inter-exchange arbitrage oppurtunities due to difference in settlement period could explain seasonality in volatility.

356

Table 181: Day of the week effect in returns and market volatility of BSE and NSE listed indices for the overall period and sub-periods

Source: Author Note:

The terms “Mon, Tue, Wed, Thur, Fri” refer to the days of the week from Monday to Friday respectively

*Significance at 5 percent level

** Significance at 1 percent level

357


(contd..)

Source: Author

Note: The terms “Mon, Tue, Wed, Thur, Fri” refer to the days of the week from Monday to Friday respectively



358


(contd..)

Source: Author

Note: The terms “Mon, Tue, Wed, Thur, Fri” refer to the days of the week from Monday to Friday respectively



359

5.2 Month-of-the-year effect results

According to Efficient Market hypothesis, returns should be equal among months and

there should be existence of no seasonal patterns between months. Thus the null

hypothesis of mean daily returns being statistically not different among months was

tested. Any violation would inturn reflect on possibility of market irregularity. In

literature, the existence of January effect is documented many times, which states that

January returns are consistently higher than the returns of any other month. There is

found to be validation for the presence of the month-of-the-year effect in some of the

examined indices during the entire sample period. The Tables 184 to 187 present the

results with respect to month-of-the-year effect in returns and volatility of all the indices

obtained from standard OLS model, GARCH model and GARCH-M models

respectively. The study reveals significant results regarding month-of-the-year effect in

Indian stock market at both broader market level and sectoral level respectively. At first,

we consider the results obtained in case of broader indices mainly BSE Sensex, CNX

Nifty and CNX Nifty Junior index as shown in Table-184. For the overall period,

significant December effect is observed in the return equation of both CNX Nifty and

CNX Nifty Junior indices even after considering the time varying market volatility in

the index returns. December is observed to have the highest returns followed by October

having the least returns. Whereas, January effect is observed in case of BSE Sensex

index considering the overall period.12

January remains to be significant in all the three

models for BSE Sensex implying that January effect is a true anomaly. However,

February effect is found no more significant under GARCH estimations but remains

significant in the returns volatility. Considering the OLS estimations, December and

October month were observed to have highest and lowest average returns respectively in

both CNX Nifty and CNX Nifty Junior index whereas, February and April months had

highest and lowest average returns in case of BSE Sensex. Considering time varying

volatility, we observe returns to be highest in May month for BSE Sensex whereas

December month retains highest returns in case of NSE indices.

12

Kaur (2004) also found higher positive returns in February and December month but did not find evidence of January effect in

Indian stock markets. Bodla and Jindal (2006) found no significant differences in the monthly Sensex returns. Fountas and segredakis (2002) found August returns to be significantly higher than april, may, October and November returns.

360

Considering the sub-periods, first sub-period examined shows presence of

significant February effect which seem to have changed pattern in second sub-period

wherein we observe significant December effect in both NSE indices but June effect in

case of BSE Sensex index13

. Pandey (2002) observed March effect in BSE Sensex for

the period 1991-2001, attributing the results to tax-loss hypothesis (Wachtel, 1942)

which are similar to our results in the first sub-period. But the patterns are observed to

change in the second sub-period and hence tax-loss hypothesis cannot be considered as

an explanation to month-of-the-year effect. Considering the results of mid-cap and

small-cap indices presented in Table-185, we can infer that April effect and December

effect remain significant in the return equation of all the three models for the overall

period and hence can be considered to be true anomalies. Combining the results of all

the three models, December is observed to have the highest returns followed by lowest

returns in January in case of BSE Mid-cap and BSE Small-cap indices, whereas in case

of NIFTY Mid-cap50 index, the highest returns were observed in April followed by

lowest returns in January14

.

Finally, considering the results of sectoral indices as presented in Tables 185 to

187, we can observe that, the coefficients for the months of August, November and

December are significant in the mean equation even after considering the time varying

volatility except for in case of S&P BSE Teck, S&P BSE O&G and CNX Infra index

respectively. Whereas, none of the months were observed to be significant in the

Standard OLS model. After considering the time varying volatility, the November and

December month mean returns are observed to be significantly higher compared to all

the months followed by January having the lowest returns in majority of the indices.

Thus, from the analysis we can notice that, the mean monthly returns are significantly

different from zero mainly in the Months of January, February, and December. The

higher Positive December mean returns followed by negative returns in the months of

January and February could be caused by a change in investor’s behavior, anticipating

January effect and March effect in Indian stock markets and other stock markets since

13

Yakob, Beal and Delpachitra (2005) considered period 2000 to 2005 as a period free of influence from asian crisis and thus a

stable period for studying seasonality. They found highest positive returns in November, and significantly lowest negative returns

in April. 14

Roll (1983) found significant differences in the returns patterns of large and small firms, especially around turn-of-the-year. Small

firm premium increases between December month of previous year and first three months of the next year.

361

the fiscal year in India starts in April and ends in March, whereas it is January to

December in other developed countries. Furthermore, a closer look at the sub-period

values reveals that, December month is statistically significant in recent period i.e.,

2002-2011. The significant February effect observed in Indian markets in the first sub-

periods seems to have changed. Thus from the analysis, we can conclude that though tax

loss hypothesis helps explain monthly effect in Indian stock markets for a brief period,

but all the indices indicate a disappearing March/April effect over the whole sample

period. Even after considering the time-varying volatility, the results reconfirm the OLS

regression results. December is found to be very significant in all the broader indices

except for BSE Sensex index wherein January is observed to be significant. whereas in

case of sectoral indices, December was observed to be significant for all the indices

except for BSE FMCG, BSE Teck, BSE O&G and CNX INFRA Indices respectively.

Thus the results obtained indicated higher integration of Indian markets than ever in the

recent period15

.

15

Schwert (2002) , Sharma & Kennedy (1977) pointed towards the disappearance of anomalies over time maybe due to rational trader exploiting the documented anomalous behavior, hence leading to efficient markets.

362

Table 184: Month of the year effect in returns and market volatility of BSE and NSE listed indices for the overall period and sub-periods

Source: Author

Note: The terms “Jan, Feb, Mar, Apr, Aug, Sept, Nov, and Dec” refer to the months of the year from January to December respectively



363

Table-185: Month of the year effect in returns and market volatility of BSE and NSE listed indices for the overall period and sub-periods

(contd..)

Source: Author Note: The terms “Jan, Feb, Mar, Apr, Aug, Sept, Nov, and Dec” refer to the months of the year from January to December respectively



364


(contd..)

Source: Author Note: The terms “Jan, Feb, Mar, Apr, Aug, Sept, Nov, and Dec” refer to the months of the year from January to December respectively



365


(contd..)

Source: Author

Note: The terms “Jan, Feb, Mar, Apr, Aug, Sept, Nov, and Dec” refer to the months of the year from January to December respectively



366

5.3 Holiday Effect

The Tables 188 to 191 show the mean (daily) index return for days around important

holidays and normal days for the overall period and sub-periods. First, the daily rate of

return around important holidays for major indices namely BSE Sensex index, CNX

Nifty index and CNX Nifty Junior index is presented in Table-188. The results point

towards disappearance of the holiday effect in the recent periods in these indices. For

the overall period, considering BSE Sensex index, the mean returns around Ganesh

Chaturthi and Bakrid holidays were found to be significantly different from other

normal trading days. Whereas, the mean returns around Dussehra and Mohurram

holidays were significant for CNX Nifty and CNX Nifty Junior indices. All the

coefficients for the above said holidays were observed to be negative in nature. On

average, the returns around Dussehra and Mohurram holidays were observed to around

five times lower when compared to mean returns around non-holiday periods. The

results obtained for the overall period seems to match the results obtained in the first

sub-period. But, disappearance of holiday effect in the second sub-period for these

indices is observed which points towards over-exploitation of the holiday effect by the

investors due to more awareness on these anomalies. It should also be noticed that the

average returns are lower when the analysis refers to the total time period, while the last

sub-period presents even lower returns which come closer to those observed in other

developed markets.

The Tables 189 to 191 presents the summary of the daily rates of return around

important holiday for sectoral indices. Considering mid-cap and small-cap indices for

the overall period, mean returns around Dussehra, Diwali and Mohurram are found to be

significantly different from non-holiday period. Negative coefficients are observed

around Dussehra and Mohurram holidays, whereas positive mean returns can be

observed around Diwali holidays. On an average, the mean returns around Dussehra and

Mohurram holidays were observed to be seven times lower when compared to mean

returns around non-holiday period. French(1980) suggested holiday returns to be

negative in nature based on the argument that the depressed Monday returns from

weekend effect are due to market closing. Whereas, the mean returns around Diwali

367

holidays was observed to be around ten times higher (Ariel,1990)16

. Further, in case of

sectoral indices also, same results re-emerge with the mean returns around Dussehra,

Diwali, Bakrid and Mohurram holidays to be significant in nature. The mean returns are

much lower (around six times lower when compared to non-holiday period) around

Dussehra, Bakrid and Mohurram holidays. Whereas, the mean returns around Diwali

holidays is significantly higher (around ten times more than mean returns around non-

holiday period). Though in the first sub-period same results were obtained, we can

notice that the holiday effect seem to disappear in second sub-period examined for all

the indices. Holiday effect seems not to be present in few indices mainly BSE CD, BSE

IT, BSE PSU, BSE AUTO, CNX IT respectively. In rest other indices, The mean returns

around major holiday mainly Ganesh chaturthi, Dussehra, Diwali, Bakrid and

Mohurram holidays are observed to be significant in nature. Thus we can observe

holiday effect to be present in all firm sizes and are more pronounced in the broader

indices than sectoral indices (Kim and Park (1994) found the same results for US

markets). Holidays were further examined based on their occurrence on weekdays and

towards specific half of the calendar month. For the study, we considered 207 holiday

dates spread across 21 years from 1990 to 2011 for nine holidays. At first, considering

the occurrence of holidays on weekdays, we find very interesting results. The results are

summarized in Figure 5 and Table-A7. In the order of the occurrence of Holidays on

weekdays, Wednesday and Friday are observed to be the days highly likely to have

holidays than rest of the other days. If we sub-divide the calendar year based on

occurrence of holidays, important holidays such as Ganesh chaturthi, Dussehra, Diwali

and Bakrid occur mainly during the later part of the calendar year i.e. between

September and December. Especially, these holidays seem to occur mainly in the second

half of the month as shown in Figure 6 and Table-A8.

Similarly, other holidays namely Mohurram, Maha Shivaratri and Rama Navami

usually occur during January and April months. Considering these holidays, the

percentage of occurrence of holidays on Tuesday is found to be highest (27%) followed

by Wednesday (20%). The holidays namely Maha Shivaratri, Rama Navami, Ramzan

16

found mean returns around pre-holidays to be significantly higher and more pronounced in nature.

368

are observed to occur towards the first half of the calendar month during the entire study

period. Thus, there is very likely chance that holiday effect is the reason for semi-month

effect and Wednesday effect as the behavior of Wednesday return behavior is found to

be dissimilar to security returns around holidays (Ariel, 1990).

Figure 5: Occurrence of major holidays on trading days of exchanges (%)

Source: Author

Figure 6: Occurrence of holidays during first half and second half of the months

for the overall study period (1990-2011)

Source: Author

8

9

10

11

12

13

14

FIRST HALF OF MONTH SECOND HALF OF THE MONTH

MAHA SHIVARATRI

RAMA NAVAMI

RAMZAN ID

GANESH CHATURTHI

DUSSERA MAHANAVAMI

DIWALI

BAKRID

GURU NANAK JAYANTHI

MOHURRAM

369

Table 188: Daily rate of return of BSE and NSE listed indices around important holidays for the overall period

Source: Author

Note:

* *and * denote Significance at 1 and 5 percent level. Coefficients of Holidays are reported in each cell. Just below the coefficients, the numbers depict t-statistics.

OTHER DAYS

0.092 -0.180 0.124 -0.313 * -0.231 -0.249 -0.349 * -0.035 0.208 0.054

0.587 -1.141 0.781 -1.985 -1.470 -1.121 -2.214 -0.205 1.319

0.095 -0.277 -0.004 -0.486 * -0.492 * -0.545 -0.534 ** 0.104 0.091 0.041

0.423 -1.231 -0.017 -2.081 -2.116 -1.688 -2.388 0.375 0.428

0.118 -0.014 0.210 -0.162 0.024 0.038 -0.114 -0.170 0.368 0.070

0.537 -0.061 0.968 -0.766 0.112 0.125 -0.512 -0.805 1.563

0.107 0.184 0.234 0.203 -0.362 * 0.301 0.103 -0.099 -0.419 ** 0.049

0.663 1.138 1.391 1.257 -2.244 1.300 0.617 -0.597 -2.522

0.403 0.435 0.048 0.042 -0.352 -0.012 -0.029 -0.261 -0.552 * 0.008

1.595 1.693 0.191 0.178 -1.512 -0.036 -0.113 -1.050 -2.200

-0.080 0.038 0.316 0.332 -0.406 0.607 0.150 0.029 -0.344 0.080

-0.380 0.179 1.378 1.469 -1.807 1.873 0.669 0.130 -1.538

-0.115 0.284 0.026 0.202 -0.325 0.512 0.000 -0.068 -0.563 ** 0.072

-0.598 1.469 0.128 1.015 -1.643 1.847 0.000 -0.352 -2.835

0.025 0.590 -0.297 0.287 -0.313 0.205 -0.320 -0.237 -0.824 ** 0.023

0.077 1.713 -0.890 0.863 -0.963 0.468 -0.938 -0.775 -2.473

-0.181 0.168 0.246 0.113 -0.364 0.745 * 0.143 0.060 -0.431 0.104

-0.772 0.719 0.967 0.452 -1.463 2.074 0.576 0.242 -1.740

MAHA

SHIVARATRI

RAMA

NAVAMI

OVERALL PERIOD

(1995-2011)

OVERALL PERIOD

(1997-2011)

BSE SENSEX

CNX NIFTY

CNX NIFTY JUNIOR

Significant HolidaysIndicesoverall period/sub-

periods

RAMZAN IDGANESH

CHATURTHI

DUSSERA

MAHANAVAMIINDICES overall period/sub-periods

OVERALL PERIOD

(1991-2011)

DIWALI BAKRID GURU NANAK

JAYANTHIMOHURRAM

SUB-PERIOD I

(1991-2001)

SUB-PERIOD II

(2002-2011)

SUB-PERIOD I

(1995-2001)

SUB-PERIOD II

(2002-2011)

SUB-PERIOD I

(1997-2001)

SUB-PERIOD II

(2002-2011)

370

Table 189: Daily rate of return of BSE and NSE listed indices around important holidays for the overall period (contd..)

Source: Author

Note: * *and * denote Significance at 1 and 5 percent level. Coefficients of Holidays are reported in each cell. Just below the coefficients, the numbers depict t-

statistics.

OTHER DAYS

-0.276 0.197 0.202 0.109 -0.484 * 0.876 ** 0.076 0.083 -0.540 * 0.109

-1.172 0.887 0.827 0.455 -2.034 2.526 0.299 0.350 -2.133

-0.371 0.247 0.210 0.056 -0.521 * 1.079 ** 0.015 0.081 -0.560 * 0.122

-1.493 1.055 0.815 0.220 -2.075 2.947 0.057 0.321 -2.095

-0.264 0.237 0.157 0.142 -0.663 * 1.021 ** 0.207 -0.063 -0.764 ** 0.066

-0.943 0.845 0.499 0.461 -2.182 2.359 0.686 -0.208 -2.535

-0.138 0.411 0.140 -0.004 -0.413 0.602 0.045 -0.033 -0.378 0.099

-0.625 1.859 0.594 -0.018 -1.790 1.802 0.197 -0.144 -1.639

0.125 0.636 -0.246 -0.231 -0.086 0.635 -0.772 0.065 -1.199 ** -0.051

0.272 1.311 -0.522 -0.480 -0.189 0.939 -1.657 0.141 -2.508

-0.215 0.450 0.254 0.049 -0.527 * 0.622 0.286 -0.067 -0.147 0.145

-0.854 1.789 0.930 0.183 -1.971 1.613 1.072 -0.249 -0.552

-0.079 0.268 0.223 0.089 -0.317 0.220 -0.597 ** 0.103 -0.505 * 0.082

-0.331 1.121 0.879 0.353 -1.272 0.607 -2.395 0.414 -2.024

0.158 0.573 0.346 0.295 0.320 0.554 -1.419 ** 0.067 -1.195 * -0.037

0.290 0.994 0.616 0.516 0.587 0.691 -2.567 0.122 -2.105

-0.157 0.273 0.202 -0.010 -0.523 0.107 -0.357 0.125 -0.325 0.118

-0.597 1.035 0.705 -0.036 -1.867 0.266 -1.280 0.447 -1.165

-0.045 -0.075 0.093 0.063 -0.215 0.507 * -0.090 0.147 -0.310 0.053

-0.264 -0.442 0.517 0.356 -1.214 1.978 -0.508 0.830 -1.756

0.536 0.360 0.569 -0.045 -0.658 -0.233 -0.235 0.157 -0.984 * 0.005

1.284 0.817 1.327 -0.103 -1.582 -0.380 -0.555 0.377 -2.267

-0.233 -0.149 -0.091 0.145 -0.066 0.743 ** -0.081 0.126 -0.127 0.068

-1.291 -0.824 -0.464 0.751 -0.345 2.682 -0.426 0.659 -0.665

DIWALI BAKRID GURU NANAK

JAYANTHIMOHURRAM

SUB-PERIOD II

(2002-2011)

S&P BSE MID-CAP OVERALL PERIOD

(2005-2011)

SUB-PERIOD II

(2002-2011)

S&P BSE CG SUB-PERIOD I

(1999-2001)

Indicesoverall period/sub-

periodsSignificant Holidays

INDICES overall period/sub-periodsMAHA

SHIVARATRI

RAMA

NAVAMIRAMZAN ID

GANESH

CHATURTHI

DUSSERA

MAHANAVAMI

OVERALL PERIOD

(2005-2011)

OVERALL PERIOD

(2005-2011)

OVERALL PERIOD

(1999-2011)

S&P BSE SMALL-CAP

CNX MID-CAP50

OVERALL PERIOD

(1999-2011)

SUB-PERIOD I

(1999-2001)

SUB-PERIOD II

(2002-2011)

S&P BSE CD

S&P BSE FMCG

OVERALL PERIOD

(1999-2011)

SUB-PERIOD I

(1999-2001)

371


Source: Author


statistics.

OTHER DAYS

0.212 0.313 -0.067 0.176 -0.371 * 0.325 -0.045 0.223 -0.705 ** 0.068

1.280 1.879 -0.378 1.009 -2.138 1.294 -0.257 1.284 -4.066

0.915 * 0.838 -0.848 0.165 -0.552 0.007 -0.499 0.519 -1.860 ** 0.049

1.926 1.672 -1.740 0.332 -1.166 0.011 -1.038 1.097 -3.769

0.007 0.266 0.185 0.094 -0.314 0.445 0.054 0.112 -0.378 * 0.074

0.041 1.653 1.061 0.547 -1.835 1.802 0.315 0.655 -2.220

-0.192 -0.263 0.112 0.443 -0.611 * 0.399 -0.592 * 0.566 -0.699 * 0.091

-0.646 -0.881 0.352 1.417 -1.961 0.884 -1.905 1.821 -2.246

-0.851 1.079 -0.142 0.346 -1.551 0.363 -1.992 * 1.485 -3.043 ** 0.143

-0.908 1.090 -0.147 0.353 -1.658 0.264 -2.098 1.588 -3.123

-0.011 -0.392 0.191 0.341 -0.257 0.394 -0.238 0.201 -0.074 0.075

-0.041 -1.492 0.670 1.215 -0.920 0.978 -0.855 0.721 -0.267

-0.107 0.140 0.256 0.161 -0.221 0.506 -0.015 -0.022 -0.386 0.083

-0.511 0.670 1.152 0.734 -1.015 1.602 -0.069 -0.099 -1.774

-0.593 -0.237 0.503 0.341 -0.501 0.693 -0.519 0.267 -0.687 * 0.044

-1.792 -0.713 1.343 0.977 -1.441 1.362 -1.496 0.768 -1.978

0.085 0.224 0.356 0.154 -0.020 0.195 0.203 0.127 -0.327 0.080

0.453 1.197 1.789 0.784 -0.103 0.688 1.041 0.649 -1.676

0.283 0.242 0.375 -0.039 -0.370 0.485 0.185 0.170 -0.531 * 0.111

1.062 0.905 1.320 -0.139 -1.330 1.201 0.666 0.611 -1.907

-0.030 0.164 -0.007 0.269 -0.293 0.819 ** 0.164 0.148 -0.402 0.089

-0.133 0.729 -0.030 1.143 -1.248 2.409 0.698 0.630 -1.715


periodsSignificant Holidays


SHIVARATRI

RAMA

NAVAMIRAMZAN ID

GANESH

CHATURTHI

DUSSERA

MAHANAVAMIDIWALI BAKRID

GURU NANAK

JAYANTHIMOHURRAM

S&P BSE O&GOVERALL PERIOD

(2004-2011)

S&P BSE TECKOVERALL PERIOD

(2001-2011)

S&P BSE AUTOOVERALL PERIOD

(2004-2011)

S&P BSE METALOVERALL PERIOD

(2004-2011)

SUB-PERIOD II

(2002-2011)

S&P BSE PSUOVERALL PERIOD

(2001-2011)

S&P BSE IT

SUB-PERIOD II

(2002-2011)

SUB-PERIOD I

(1999-2001)

OVERALL PERIOD

(1999-2011)

S&P BSE HC

OVERALL PERIOD

(1999-2011)

SUB-PERIOD I

(1999-2001)

372


Source: Author


statistics.

OTHER DAYS

0.079 -0.015 0.129 0.457 -0.605 * 0.172 -0.171 0.374 -0.514 0.115

0.265 -0.050 0.415 1.484 -1.971 0.388 -0.556 1.218 -1.675

0.213 0.913 0.016 0.614 -0.985 -0.200 -0.314 0.560 -1.255 ** 0.235

0.403 1.665 0.030 1.156 -1.876 -0.262 -0.579 1.066 -2.365

-0.002 -0.489 0.219 0.296 -0.342 0.386 -0.260 0.225 -0.097 0.039

-0.006 -1.387 0.573 0.785 -0.912 0.713 -0.697 0.601 -0.260

-0.449 0.098 0.368 0.539 * -0.314 0.583 0.246 -0.082 -0.394 0.101

-1.826 0.397 1.393 2.079 -1.217 1.546 0.955 -0.316 -1.528

-0.131 0.408 0.218 0.301 -0.727 ** 0.748 0.251 -0.073 -0.448 0.076

-0.456 1.418 0.675 0.957 -2.332 1.684 0.809 -0.236 -1.450

Significant Holidays


SHIVARATRI

RAMA

NAVAMIRAMZAN ID

GANESH

CHATURTHI

DUSSERA

MAHANAVAMIDIWALI BAKRID

GURU NANAK

JAYANTHIMOHURRAM

CNX INFRAOVERALL PERIOD

(2004-2011)

OVERALL PERIOD

(1999-2011)

BANK NIFTYOVERALL PERIOD

(2000-2011)

CNX IT SUB-PERIOD I

(1999-2001)

SUB-PERIOD II

(2002-2011)


periods

373

5.4 HALF-MONTH EFFECT:

The Tables 192 to 194 presents the mean daily returns over the first half of the month

for each index and the mean daily return during the rest of the month. According to

Ariel’s (1987), first half of the month is significantly higher when compared to the

second half of the month. The Table-192 presents the significant semi-month and

percentage of positive months having the significant semi-month for broader indices.

We can observe that the first half of the month returns are significantly higher when

compared to second half of the month except in case of BSE Sensex (second sub-period)

and CNX Nifty (for both sub-periods). For the first sub-period, BSE Sensex index has

positive average returns during the first half (0.085 percent) and negative average

returns during the second half of the month (-0.0016). The mean returns during the first

half of the month is higher compared to the second half. The percentage of positive

months is observed to be significantly higher in the first half of the month when

compared to second half of the month. But, in the second sub-period examined the

average returns during first and second half are positive with second half average daily

returns higher than first half average returns. The percentage of positive days are

observed to be significantly higher in the second half of the month. In case of CNX

Nifty index, the average returns as well as the percentage of positive months during the

second half of the month were observed to be significantly higher compared to first half

of the month in both the sub-periods. The CNX Nifty Junior, BSE Mid-cap index, BSE

Small-cap index and NIFTY Mid-cap50 index have positive average returns during the

first half when compared to second half of the month. The percentage of positive month

is also observed to be higher in the first half of the month in all the indices. The Tables

193 and 194 present the results of semi-month effect for all the sectoral indices. All the

BSE and NSE sectoral indices are observed to have positive average returns during both

halves. However, the index returns during the second half of the month are higher

compare to the other half. This is in case of all the BSE listed sectoral indices except for

BSE FMCG index and BSE TECK index have average returns and percentage of

positive months during the second half of the month to be relatively positive and higher

than the first half of the month. Whereas in case of NSE listed sectoral indices, the

results are contrasting to the previous results. Similar to the results obtained for BSE

374

sectoral indices, the CNX IT, Bank Nifty and CNX Infra indices are observed to have

positive average returns during both halves of the calendar month. However, the index

returns during the first half of the month are higher compared to the other half. From

literature, we know that most of the developed country indices seem to hold higher than

average returns during the first half of the month which is similar to the results obtained

in NSE listed indices, mid-cap and small-cap indices, but we also know that, the indices

from the emerging economies, however, show reversed effect which is in accordance

with the results obtained for majority of the indices. Overall, the evidence for the semi-

month anomaly is significant.

5.5 TURN-OF-THE-MONTH EFFECT RESULTS

The Tables 192 to 194 as shown in previous pages also presents the summary of the

turn-of-the-month (Day -1 to Day+3) mean daily returns for all the indices considered

for overall period and sub-periods respectively. The mean daily returns around the turn-

of-the month for BSE and NSE listed broader indices are observed to significantly

higher when compared to other days of the month as shown in Table-192. Considering

BSE Sensex and CNX Nifty index, the daily mean returns were observed to be

significant higher in the second sub-period. The first three days of the months including

the last days of the previous months are found to be significant higher when compared

to other days of the month mainly in the second sub-period examined. Accompanied

with the increasing daily mean returns, the percentage of positive returns is observed to

be significantly higher towards the turn-of-the-month. The percentage of positive returns

is observed to be on average around seventy percentage in case of both the indices. The

percentage can be noticed to be higher in the second sub-period examined when

compared to the first sub-period. Similarly among the broader indices mainly CNX

Nifty Junior, BSE Mid-cap, BSE small-cap and NIFTY Mid-cap50, we can observe the

same trend for the overall period. The mean daily returns around turn-of-the-month are

observed to significantly higher with daily returns increasing from last day of the

previous month (Day -1) until second day of the present month (day +2) after which the

returns decline substantially. Thus turn-of-the-month mean daily returns can definitely

be profitable if buy-hold strategy is followed by the investors. The sum of the mean

375

daily returns for all four days appear to be positive in all the broader indices with

percentage of positive returns substantially supporting the results. Thus on an average,

an investor can make a gain of around two percentage adopting buy-hold strategy only

over the short span of four days towards the turn-of-the-month. The percentage of

positive returns was observed to higher in case of mid-cap and small-cap indices. The

mean daily returns around turn-of-the-month for sectoral indices is presented in Tables

193 and 194 respectively. The results obtained for sectoral indices point towards

normalized returns towards the turn-of-the-month when compared to other days. The

mean daily returns around all the sectoral indices are observed to be high but not

statistically significant when compared to daily returns of other days. The total average

returns earned over four days towards the turn of the month appear to be less when

compared to broader indices ranging from 0.8 percent to 1.8 percent. Whereas, the

percentage of positive returns towards the turn-of-the-month seem to be significantly

higher mainly towards the first and second day of the present month. Thus, when

compared to sectoral indices, broader indices seem to reveal anomaly among daily

returns towards the turn-of-the-month. The sectoral indices have minor or no indication

for turn-of-the-month effect, while broader indices especially mid-cap and small-cap

indices mean daily returns seem to be stronger during the turn-of-the-month. Thus, turn-

of-the-month effect seem to be mostly present in the broader indices.

376

Table-192: Daily stock market returns for BSE and NSE listed broader indices at the turn of the month and semi-month for the overall

period and sub-periods

Source: Author Note: *Significance at 5 percent level


Day -1 Day +1 Day+2 Day+3 Day(-1,+3)

0.2500 0.1640 0.5012 0.1386 1.0538

67.2700 64.9000 68.0800 52.6300 63.2200

0.4558 0.5166 0.3558 0.2087 1.5369

65.96* 74.39** 73.17** 63.41** 69.2325

0.1850 0.1560 0.427* 0.1490 0.9170

60.0000 58.9500 67.0000 51.0000 59.2375

0.4280 0.521** 0.346* 0.2050 1.5000

65.96* 76.8300 72.0000 63.4100 69.5500

0.3240 0.471** 0.369* 0.1460 1.3100

64.1* 68.89** 73.33** 58.8200 66.2850

0.5890 0.6070 0.4410 0.3144 1.9514

67.5* 78.87** 76.71** 71.83** 73.72**

0.5000 0.7550 0.3590 0.2786 1.8926

67.5* 78.87** 78.08** 70.42** 73.72**

0.4700 0.652** 0.542** 0.3450 2.0090

67.57* 76.56** 74** 70.31** 72.1100

First Half (58.28)**

Second Half(56.71)**

Second Half(58.18)**

Second Half (58)**


Daily stock market returns for BSE and NSE listed indices at the turn of the month and semi-month for the overall period

and sub-period

Mean daily return(%)

positive (%)

overall period/sub-periods Turn of the month

positive (%)

INDICES

Significant semi-month

(percentage of positive

months)

SUB-PERIOD I

(1991-2001)

SUB-PERIOD II

(2002-2011)

SUB-PERIOD I

(1995-2001)

BSE SENSEX


CNX NIFTY JUNIORMean daily return(%)

positive (%)


positive (%)


OVERALL PERIOD

(1997-2011)

SUB-PERIOD II

(2002-2011)

S&P BSE SMALL-CAP

INDEX


positive (%)

S&P BSE MID-CAP INDEXMean daily return(%)

positive (%)

OVERALL PERIOD

(2005-2011)First Half (63.32)**

OVERALL PERIOD

(2005-2011)First Half (64.54)**

CNX MID-CAP50 INDEXMean daily return(%)

positive (%)

OVERALL PERIOD

(2005-2011)First Half (60.54)**

CNX NIFTY

positive (%)

377

Table-193: Daily stock market returns for BSE and NSE listed indices at the turn of the month and semi-month for the overall period and

sub-periods (contd..)




0.4270 0.5500 0.2745 0.4436 1.6951

61.9000 70.75** 65.4200 67.29* 66.3400

0,733 0.4680 0.3060 0.3106 1.0846

62.0000 67.92** 66.3600 65.4200 65.4250

0.4400 0.1500 -0.0840 0.2950 0.8010

65.08* 67.92** 58.8800 62.62* 63.6250

0.4650 0.2440 0.2710 0.3540 1.3340

65.08* 61.3200 71.03** 64.49** 65.4800

0.4310 0.5850 0.2660 0.2060 1.4880

61.9000 64.1500 59.8100 60.7500 61.6525

0.4530 0.6154 0.4440 0.2630 1.7754

68.25** 73** 66.36* 66.36** 68.4925

0.4160 0.4540 0.2750 -0.0130 1.1320

63.7900 65.3100 60.2000 59.1800 62.1200

0.7440 0.3810 0.2360 0.4010 1.7620

76** 66.04* 71.03** 63.5500 69.1550

0.4140 0.4333 0.4360 0.2820 1.5653

65.0000 68.8700 67.0000 64.4900 66.3400

0.6950 0.4960 0.3760 0.2090 1.7760

65.0800 66.0000 64.4900 58.8800 63.6125

OVERALL PERIOD

(1999-2011)Second Half (57.23)**


and sub-period (contd..)

INDICES overall period/sub-periods



months)

Turn of the month

S&P BSE CD INDEX

OVERALL PERIOD

(1999-2011)First Half (55.61)**

S&P BSE CG INDEX


positive (%)

OVERALL PERIOD

(1999-2011)Second Half (55.62)**


positive (%)

S&P BSE HCMean daily return(%)

positive (%)

OVERALL PERIOD

(1999-2011)

OVERALL PERIOD

(1999-2011)

Second Half (58.71)**


S&P BSE FMCG Mean daily return(%)

positive (%)

S&P BSE PSUMean daily return(%)

positive (%)

OVERALL PERIOD

(2001-2011)

OVERALL PERIOD

(2001-2011)


First Half (54.9)**

S&P BSE ITMean daily return(%)

positive (%)

S&P BSE AUTOMean daily return(%)

positive (%)

OVERALL PERIOD

(2004-2011)

OVERALL PERIOD

(2004-2011)



S&P BSE TECKMean daily return(%)

positive (%)


S&P BSE O&GMean daily return(%)

positive (%)

OVERALL PERIOD

(2004-2011)Second Half (52.33.38)**

S&P BSE METALpositive (%)

378

Table-194: Daily stock market returns for BSE and NSE listed indices at the turn of the month and semi-month for the overall period and

sub-periods (contd..)




0.3240 0.4710 0.3690 0.1460 1.3100

64.1* 68.89** 73.33** 58.5200 66.2100

0.3690 0.6960 0.4610 0.3610 1.8870

61.0200 72.4500 70.4100 61.6200 66.3750

0.5350 0.6040 0.4150 0.2720 1.8260

67.5700 76.5600 71.0000 71.8800 71.7525

OVERALL PERIOD

(1997-2011)First Half (57.93)**


and sub-period (contd..)

INDICES overall period/sub-periods



months)

Turn of the month

BANK NIFTYMean daily return(%)

positive (%)

OVERALL PERIOD

(2000-2011)

OVERALL PERIOD

(2004-2011)



CNX IT Mean daily return(%)

positive (%)

CNX INFRAMean daily return(%)

positive (%)

CHAPTER 5 FINDINGS OF THE STUDY -...

Documents

Transcript of CHAPTER 5 FINDINGS OF THE STUDY -...