International Journal of Advanced Research in Management (IJARM)
Volume 7, Issue 1, Jan-April (2016), pp. 88–95, Article ID: IJARM_07_01_010
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© IAEME Publication
“WEEK-END EFFECT”: WHAT IS
HAPPENING AFTER MODI GOVERNMENT
CAME INTO POWER?
Biju Thomas Muttath
Head-Finance (Star Group),
Research Scholar, R&D Centre,
Bharathiar University, Coimbatore - 46, T.N, India
Dr. Assissi Menachery
Professor, Loyola Institute of Technology & Science,
K.K Dist, T.N, India
ABSTRACT
The returns in stock market can be attributed to fundamental factors and
non-fundamental factors. The effect of fundamental factors such as P-E ratio,
dividends and ROI can be explained using current theories. However, there
are some non-fundamental factors whose effect on the stock market is difficult
to be explained. One among the non-fundamental factors that have an
anomalous effect on the stock market is the ‘Weekend effect’. Weekend effect
is used to describe the phenomenon in financial markets in which stock returns
on Mondays are often significantly lower than those of the immediately
preceding Friday. This research employs data pertaining to index based
securities of National Stock Exchange, from 01-06-2014 to 15-04-2016. This is
to determine whether weekend effect is evident in the Indian stock market after
the present government came into power and to further validate whether
weekend effect can be considered as a possible decision making variable for
day traders and short term investors in the present economic and political
scenario.
Key words: Seasonal Anomalies, January Effect, Weekend Effect, Nifty
Cite this Article: Biju Thomas Muttath and Dr. Assissi Menachery, “WeekEnd Effect”: What Is Happening After Modi Government Came Into Power?.
International Journal of Advanced Research in Management, 7(1), 2016, pp.
88–95.
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1. INTRODUCTION
Seasonal variations in production and sales are a well-known fact in business.
Seasonality refers to regular and repetitive fluctuation in a time series which occurs
periodically over a span of less than a year. The main cause of seasonal variations in
time series data is the change in climate. Stock returns exhibits systematic patterns at
certain times of the day, week or month. Similarly, some days of the week provides
lower returns as compared to other trading days i.e. days of the week effect. The
desire of individuals for liquidity may be thought to change from day to day and from
month to month. One might presume that such patterns would be relatively
unimportant. According to the notion of efficient markets, such patterns should be
quite minor, since they are not suggested by any asset pricing model. However,
studies indicate that at least two patterns are significant: “the January effect” and “theday-of –the- week effect”. The January effect refers that the average return in January
was higher than the average return in any other month. The Weekend effect (also
known as The Monday effect, the-day-of-the week effect or Monday seasonal) refers
to the tendency of stocks to exhibit relatively large returns on Fridays compared to
those on Mondays. Various studies (Kenneth French -1980, Richard J. Rogalski-1984,
Lawrence Harries- 1986) have evidenced that the average return on Monday was
negative [1,2,3].
It is important to know whether there are variations in volatility of stock returns
by day of the week patterns and whether a high or low return is associated with a
corresponding high or low return for a given day. Some theories that explain the
effect attribute the tendency for companies to release bad news on Friday after the
markets close to depressed stock prices on Monday. Others state that the weekend
effect might be linked to short selling, which would affect stocks with high short
interest positions. Alternatively, the effect could simply be a result of traders' fading
optimism between Friday and Monday. Having such knowledge may allow investors
to adjust their portfolios by taking into account day of the week variations in
volatility.
In 1942,Watchel reported the seasonality in stock price for the first time [4]. The
article “ The Behaviour of Stock process on Fridays and Mondays’ by Cross Franc in
1973 explains the S& P composite rose on 523 Fridays or 62% of all Fridays whereas
it rose on Mondays only 333 times or on 39.5% of all Mondays [5]. Early studies
looked at the average daily return on NYSE- listed securities and found that the return
on Monday was found to be much lower than the average return on any other day of
the week. “Weekend Effect of Stock Returns in the Indian Market”, a study conducted
by Ankur Singhal and Vikram Bahure conclude that the daily observed stock returns
should depend on the day of the week and that there is requirement for adjustment for
interest gains on certain days because of the effects of market sentiments and the
settlement cycle [6]. Results suggest that future examinations of the stock market of
the period from April 2003-April 2008 will have residual daily effects, even after the
adjustments that are the unexplained part of the weekend effect. Anup and Kishore
Tandon, (1994) “Anomalies or illusions? Evidence from stock markets in eighteen
countries”, examines five seasonal patterns in stock markets of eighteen countries: the
weekend, turn-of-the-month, end-of-December, monthly and Friday-the-thirteenth
effects [7]. They observed a daily seasonal in nearly all the countries, but a weekend
effect in only nine countries. The last trading day of the month has large returns and
low variance in most countries. Many countries have large December pre-holiday and
inter-holiday returns. The January returns are large in most countries and a significant
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Biju Thomas Muttath and Dr. Assissi Menachery
monthly seasonal exists in ten countries. A note on “information seasonality and the
disappearance of the weekend effect in the UK stock market” concludes that the
weekend effect in UK stock prices has disappeared in the 1990s. “A new look at the
Monday effect”, article by Wang, Ko, Yuming LI and John Erickson(1997),
documented that expected stock returns vary with the day - of - the week [8]. In the
article, they show that the well-known Monday effect occurs primarily in the last two
weeks, ie, fourth and fifth weeks of the month. In addition, the mean Monday return
of the first three weeks of the month is not significantly different from zero.
“New evidence in the Monday seasonal in stock returns” a study by Kamara
Avraham (1997) explains equity derivatives and the institutionalization of equity
markets affect the Monday seasonal [9]. The seasonal in the Standard and Poor's 500
(S&P) was declines significantly over 1962-93. This decline is positively related to
the ratio of institutional to individual trading volume. In contrast, the seasonal for
small stocks does not decline and is unaffected by institutional versus individual
trading. Higher trading costs sustain the seasonal in small stock, and unlike the S&P,
these costs are not lower for institutions than for individuals. Futures minus spot S&P
returns exhibit a reverse seasonal. Informed traders use the less costly market to
exploit the seasonal. Some researchers have apparently been surprised to discover
that the distribution of stock returns depends on the day of the week. French Kenneth,
in testing whether daily stock returns are generated by a trading time or calendar time
hypothesis, provided convincing evidence of a negative market return on Mondays
[1]. As French carefully notes, this finding runs counter to both hypotheses, since a
trading time view would have expected stock returns equal on different days, and a
calendar time view would have higher expected returns on Monday to compensate for
the longer holding period. The paper offers a partial explanation for the apparently
puzzling discovery of different daily returns. French argues that the expected stock
returns as measured, for example, from closing prices, should depend on the day of
the week. In general, it is argued that the expected returns on Mondays should be
lower than would be implied simply by a trading time or calendar time model, and the
returns on Fridays should be higher. In addition, holidays will have complex effects
on stock returns on other days of the week. The argument is based on the delay
between trading and settlements in stocks and in clearing checks. However, results of
this effect have not provided uniform results. Recent studies by Brusa, Liu and
Shulman (2005) and Gu (2004) reported that of late the negative weekend effect has
reversed and become a positive Monday effect [10, 11]. This is termed ‘reverse
weekend effect’.
Although several studies on weekend effect exists, we consider this study very
unique in the present economic, political and social scenarios. Presently India is a
country with an average growth rate of 7.0% to 7.5%. India is undergoing a unique set
of structural, financial and fiscal reforms after Modi government came into power.
The nifty crossed the historical 7500 mark after Modi Government came in to power
and struggles to sustain that position. Moreover according to the Governor of RBI, Dr.
Reguram Rajan, “RBI is looking to cut interest rates based on good monsoon and
favorable season. At this juncture, it would be interesting to understand the seasonal
anomalies of the Indian Stock Market especially the “week end effect”, to understand
whether after June 2014, whether the general presumption prevails, returns on Friday
would be more than that of Monday. Similarly return on Friday would be more than
that of the average weekly return.
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2. OBJECTIVES OF THE STUDY
1. To observe and study the returns obtained on Fridays and immediate Mondays with
respect to the closing price of the shares.
2. To observe and study the returns obtained on Friday and the average return obtained
during the week with respect to closing price of the shares.
HYPOTHESES
1. The average return obtained remain to be homogeneous with respect to Friday and
Monday.
2. The average return obtained remain to be homogeneous with respect to Friday and the
weekly average.
2.2. Methodology
2.2.1. Sample
Nifty fifty shares form the population of the study. Further the company name was
categorized as per the alphabetical order. The researcher collected data from the
National Stock Exchange (NSE). Thus researchers took 50% of the index based
securities in NSE (25 Numbers) and its daily closing prices from 01-06-2014 to 1504-2016 have been considered for analysis. Simple random sampling method has been
adopted to select the individual shares to analysis the historical prices of shares.
2.2.2. Technique
Data collected were analyzed using various statistical tools and the results are
presented. “Z” test is used to test the significant difference between returns on Fridays
and succeeding Mondays. During discussion, attention has been given in arriving at a
conclusive perspective on the analysis, hypotheses testing and interpretation of data.
The results are discussed in detail.
2.3. ANALYSIS AND RESULTS
2.3.1. Friday and Monday Returns
The data collected were analyzed using various statistical tools, and the results are
presented. Null hypotheses formulated for the purpose of present investigation are put
together using the inferential statistical tools. Z-test is used to find out the similarity
or difference between two different groups such as ‘Friday and Monday’. During
discussion, attention has been given in arriving at a conclusive perspective on the
analysis, hypothesis testing and interpretation of data related to the variables. The
results are discussed in detail.
2.3.1.1. Test of Significance: Friday and Monday Returns
The mean return obtained on Friday, Monday and Z value were worked out as per
Table 1 for the twenty five shares during the period between 1/06/2014 to 15/04/2016
selected randomly from Nifty fifty. A comparison has been done between the
different groups. It is observed that there is no significant difference between the
mean scores of the two different groups (Friday and Monday).
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Table 1 Observed “Z” Values (Friday & Monday Returns)
Mean
Mean
Return
Return
(Friday) (Monday)
1
ACC Ltd.
1428.14
1429.27
2
Ambuja Cements Ltd.
222.15
222.66
3
Axis Bank Ltd.
603.29
602.98
4
Bajaj Auto Ltd.
2339.89
2334.28
5
Bank of Baroda
424.17
434.50
6
Bharti Airtel Ltd.
366.47
366.15
7
Coal India Ltd.
356.31
357.34
8
Dr. Reddy's Laboratories Ltd.
3324.04
3323.00
9
HCL Technologies Ltd.
1208.20
1215.22
10
Hindustan Unilever Ltd.
814.33
812.28
11
Idea Cellular Ltd.
150.39
150.87
12
Infosys Ltd.
2065.37
2075.77
13
I T C Ltd.
338.46
338.32
14
Larsen & Toubro Ltd.
1532.24
1535.80
15
Mahindra & Mahindra Ltd.
1254.75
1253.51
16
Maruti Suzuki India Ltd.
3654.73
3643.40
17
NTPC Ltd.
138.61
138.81
18
Oil & Natural Gas Corporation Ltd.
311.00
313.09
19
State Bank of India
816.83
845.77
20
Sun Pharmaceutical Industries Ltd.
852.39
850.29
21
Tata Consultancy Services Ltd.
2481.57
2503.09
22
Tata Motors Ltd.
445.77
446.72
23
Tata Power Co. Ltd.
77.18
77.89
24
Tata Steel Ltd.
353.67
355.07
25
UltraTech Cement Ltd.
2812.90
2806.85
*NS – Not Significant at 0.05 Significance level
Sl.
No
Company Name
‘Z’
value
0.455
0.399
0.503
0.628
0.392
0.536
0.381
0.509
0.429
0.595
0.419
0.461
0.523
0.431
0.575
0.569
0.429
0.391
0.388
0.588
0.148
0.453
0.302
0.449
0.608
Significant/
Not
significant
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
2.3.2. Friday and Weekly Average Return
The data collected were analyzed using various statistical tools, and the results are
presented. Null hypotheses formulated for the purpose of present investigation are put
together using the inferential statistical tools. Z-test is used to find out the similarity
or difference between two different groups such as ‘Friday and Average weekly
return’. During discussion, attention has been given in arriving at a conclusive
perspective on the analysis, hypothesis testing and interpretation of data related to the
variables. The results are discussed in detail.
2.3.2.1 Test of Significance: Friday and Weekly Average Return
The mean return obtained on Friday, Weekly average return and Z value were worked
out as per Table 2 for the twenty five shares during the period between 1/06/2014 to
15/04/2016 selected randomly from Nifty fifty. A comparison has been done between
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the different groups. It is observed that there is no significant difference between the
mean scores of the two different groups (Friday and Weekly average return).
Table 2 Observed “Z” Values (Friday &Weekly Average Returns)
Mean
Return
(Friday)
1428.14
222.15
603.29
2339.89
Mean
Return
(Week)
1428.54
222.19
603.25
2336.24
5
Bank of Baroda
424.17
6
Bharti Airtel Ltd.
366.47
7
Coal India Ltd.
356.31
8
Dr. Reddy's Laboratories Ltd.
3324.04
9
HCL Technologies Ltd.
1208.20
10
Hindustan Unilever Ltd.
814.33
11
Idea Cellular Ltd.
150.39
12
Infosys Ltd.
2065.37
13
I T C Ltd.
338.46
14
Larsen & Toubro Ltd.
1532.24
15
Mahindra & Mahindra Ltd.
1254.75
16
Maruti Suzuki India Ltd.
3654.73
17
NTPC Ltd.
138.61
18
Oil & Natural Gas Corporation Ltd.
311.00
19
State Bank of India
816.83
20
Sun Pharmaceutical Industries Ltd.
852.39
21
Tata Consultancy Services Ltd.
2481.57
22
Tata Motors Ltd.
445.77
23
Tata Power Co. Ltd.
77.18
24
Tata Steel Ltd.
353.67
25
UltraTech Cement Ltd.
2812.90
*NS – Not Significant at 0.05 Significance level
429.58
366.56
356.74
3318.76
1210.67
813.37
150.69
2060.99
338.00
1530.50
1252.77
3650.76
138.70
311.35
834.01
850.21
2497.67
446.40
77.53
354.41
2810.56
Sl No
1
2
3
4
Company Name
ACC Ltd.
Ambuja Cements Ltd.
Axis Bank Ltd.
Bajaj Auto Ltd.
‘Z’ value
0.484
0.493
0.501
0.584
0.442
0.489
0.450
0.545
0.474
0.546
0.448
0.516
0.587
0.533
0.619
0.524
0.471
0.481
0.432
0.594
0.219
0.469
0.400
0.473
0.542
Significant/
Not
significant
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
NS*
2.3.3. Discussion
The calculated Z value, range is in between 0.148 (TCS) and 0.628 (Bajaj Auto
Limited). In the case of all twenty five shares there is no significance difference
between the mean return obtained on Friday with respect to the mean return obtained
on Monday. Hence the null hypothesis is accepted in the case of all twenty five
companies. Though statistically not significant, only in eight shares the mean scores
obtained on Fridays are greater than the mean scores obtained on Mondays. The
tendency of the shares to offer higher return on Fridays compared to immediate
Mondays is the essence of weekend effect. While comparing the mean return on
Fridays with mean return on immediate Mondays only 8 shares (Bajaj Auto, Bharati
Airtel, DR Reddies, Hindustan Unilever, Mahindra & Mahindra, Maruti Suzuki, Sun
Pharma and Ultratech Cement Co) satisfied within the theoretical frame. This result
support the studies of Agarwal Anup and Kishore Tandon that week end effect from
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UK stock prices disappeared in the 1990s [7]. The result also support the studies of
Brusa, Liu,Shulman and Gu [10,11] that explains the reverse weekend effect.
However, the result does not support the studies of Ankur Singhal &Vikram Bahure
[6] that happened in Indian stock market. During the period of 2003-2008, they
observed that there was residual week end effect in share price in Indian stock market.
This is in contrast to the present study.
In the case of Friday returns with respect to the average weekly return. The
calculated Z value, range is in between 0.219 (TCS) and 0.619 (Mahindra &
Mahindra Ltd). In the case of all twenty five shares there is no significance difference
between the mean return obtained on Friday with respect to the mean return obtained
on Monday. Hence the null hypothesis is accepted in the case of all twenty five
companies. Though statistically not significant, only in eight shares the mean scores
obtained on Fridays are greater than the mean weekly average scores. Whereas while
comparing the mean return on Friday with mean return of week, only 8 share (Bajaj
Auto, DR Reddies, Hindustan Unilever, Infosys, ITC, L&T, Maruti Suzuki and
Ultratech Cement Co) produced more return on Fridays. The higher Friday return
apparent in the above cases was too spineless to produce considerable return on
investment. The test of hypotheses reveals that the impact of the day of the week
effect in share prices were not significant to generate above average return on Fridays.
In this context the impact of weekend effect in Indian stock market is skeptical.
3. CONCLUSION
The present study conclude that the ‘Weekend Effect” is not apparent and it cannot be
inferred that the return on Fridays will be more than the return on Mondays. Similarly,
return on Fridays is also not more than the average return obtained during the week.
This result support the studies of Agarwal Anup and Kishore Tandon that week end
effect from UK stock prices disappeared in the 1990s [7]. The result also support the
studies of Brusa, Liu,Shulman and Gu [10,11] that explains the reverse weekend
effect. Further studies are required to substantiate that why weekend effect disappear
or reverse when time emerges or when nations, economies and culture progress. If
this has happened in U.K after 1990’s, the same is happening in India after 2014.
Future studies are required to substantiate these findings. Does changes in political,
economic and fiscal scenario has an impact on seasonal anomalies? Does Information
asymmetry has an impact of Seasonal anomalies? Does emergence of economies has
an influence on Seasonal anomalies? All this questions may be answered with an
international survey of cross-national countries integrated with time series analysis.
These questions provide potential for future research.
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[2]
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[4]
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February,39(5):1603–14
Harris Lawrence (1986), A Transaction Data Study of Weekly and Intradaily
Patterns in Stock Returns, Journal of Financial Economics, 16, 99–117.
Wachtel, S.B (1942), certain observations on seasonal movements in stock prices,
Journal of Business 15,184–93.
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“Week-End Effect”: What Is Happening After Modi Government Came Into Power?
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Web site: www.nseindia.com, National Stock Exchange (NSE), India.
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