Calendar Effects in Fifty-five Stock Market Indices

Social Science Research Network, 2009

This study examines the calendar effects in 55 Stock market exchange indices around the globe. The effects which are examined are the turn of the Month effect, day of the Week effect, Month of the Year effect and semi Month effect. The methodology followed is the test hypothesis with bootstrap simulated t statistics. A seasonality test is to investigate if there is more certain seasonality on expected returns or in volatility. The conclusion is that we reject all calendar effects in a global level, except from the turn of the Month effect, which is presented in 36 stock indices. Moreover there is higher seasonality in volatility rather on expected returns, concerning the day of the week and the month of the year effects. One of the first studies about the turn of the month effect was the paper by Ariel (1987), who daily data for Center for Research in Security Prices (CRSP) value weighted and equally weighted stock index returns from 1963 through 1981 and he found that there are significant differences between the first and second half of the month stock average returns, where the average returns of the last half of month are not different from zero, while in the first half are significant. Cadsby and Ratner (1992) obtain daily data of eleven indices from ten countries and they define the last and the first three trading days of each month as the turn of the month effect. Cadsby and Ratner (1992) found that there is the turn of the month effect is six countries. Jaffe and Westerfield (1989) obtain daily returns of stock market indices for four countries. They examined if there is significant difference between intervals [ 9, 2] and [ 1, +9]. The authors found that there are higher returns of the first half of the month than the returns of the last half of the month in three countries. Ziemba (1991) examines daily returns for NSA Japan during 1949 1988 for the intervals [ 5, +2] and [ 5, +7] and applying descriptive and t statistics finds that in these intervals returns are higher than any other period. McConnell and Xu (2008) define the turn of the month interval as [ 1, +3] and they found that the specific calendar effect exists for USA and for other 30 out of 34 countries except Argentina, Colombia, Italy, and Malaysia. Martikainen et al. (1995) examine the interval [ 1, +4] as the turn of the month and they apply t statistics to test if the mean returns of this interval are positive and significant greater different from zero. Martikainen et al. (1995) found that these positive and significant returns are observed in the interval [ 5, +5]. Kunkel et al. (2003) found that there are positive mean returns in every country in the [ 1, +3] interval than any other interval. Aggarwal and Tandon (1994) tested the turn of the month ,who found that there are significantly higher returns in the interval previous, [ 1, +3] interval in ten out of eighteen countries. Marquering, et al. (2006) examined if each calendar effect and anomaly is still present and valid after the publication of papers about them. Holiday, day of the week, January, time of the month, turn of the month and size effect are the calendar anomalies that authors examine in their paper. The authors found that only the turn of the month effect is not disappeared. Tan and Tat (1998) conclude that all effects exist , but are diminishing through time. Aggarwal and Tandon (1994) test the day of the week found that Monday returns are negative in thirteen countries, but are significant only in seven countries. Also they found that Friday returns are significantly positive in almost all countries. Agathee (2008) examined the day of the week effect, who finds positive and significant ordinary least squares regression coefficients on Mondays, Wednesdays, Thursdays and Fridays, but however Fridays returns are the highest. Mills et al. (2000) haven't found Monday effect , but a Tuesday effect similar to other papers is presented. Aggarwal and Rivoli (1989) find that Monday and Tuesday returns are lower than the overall average, while the Friday returns are higher, as also the volatility measured by the standard deviation is highest on Mondays. So in addition to the Monday effect, Aggarwal and Rivoli (1989) find a Tuesday effect in four Asian markets, which examined. Draper and Paudyal (2002) FT All Share index and FTSE 100 Index from the beginning of 1988 until December 1997, and they found that Monday returns are negative and generally the returns of the other four days of the week are significantly higher Arsad and Coutts (1997) study the day of the week , the month of the year and the holiday effect using daily returns of FT 30 Index in UK from 1 July 1935 through 31 December 1994, splitting the whole sample in 12 sub samples. Arsad and Coutts (1997) use OLS estimation and the regress daily returns on dummies corresponding on the trading days of the week. Marquering, et al. (2006) found that Monday effect doesn't exist , but a Tuesday effect similar to other papers is presented. Holden et al. (2005) found some significant calendar anomalies , among them the Monday effect with negative returns. Tonchev and Kim (2004) find a weak evidence for the day of the week effect in Slovenia, and specifically Monday, but in the opposite direction. Floros (2008) rejects January effect for all the three indices which examined and he finds higher returns over other months rather January, but estimating coefficients are statistically insignificant, except significant negative returns in June for all indices. Mills et al. (2000) examine the month effect and found significant higher average returns on January and February. Choudhry (2001) reports significant negative returns in March and July for UK, while significant positive returns in February, August, September and December and significant negative returns in June and October were found for Germany. Aggarwal and Rivoli (1989) investigate the month-of the year effect and they find that January effects exists. Arsad and Coutts (1997) use OLS estimation with dummy independent variables representing the day belonging in a specific month, who found January displays significant positive average returns for FTSE 100 after the introduction of capital gains tax in 1965. Marquering, et al. (2006) report in their results significant higher average returns in January and February. Alagidede and Panagiotidis (2006) examine the month of the year effect and they found mean monthly significant returns in February, March, April and July, with the highest returns reported in April. Floros (2008) used the General ASE index, FTSE/ASE 20 and FTSE/ASE Mid 40 indices to test the semi month effect and he finds that there are higher returns over the first fortnight for the General ASE index. The opposite happens for the other two indices FTSE/ASE 20 and FTSE/ASE Mid 40. Mills et al. (2000) investigate the trading month effect and they report that the average returns on days prior the stock market vacations for General index and the 90% of its constituent stocks as average returns in the first fortnight of each trading month for the General index and the 70% of its constituent stocks are significant higher. Marquering et al. (2006) found that significant higher average returns are presented during the first fortnight of the month. Balaban and Bulu (1996)

A curious seasonal anomaly found in finance is the turn of the month effect, where the daily mean return of stock market at the end of a month and beginning of a month is significantly higher than the average daily return of all the days of a month. There have been evidences that certain months in a year deliver significantly higher returns. Similar anomalies are found for week days also, where some days in a week deliver above average returns. Seasonal anomalies for researchers have been a subject of great interest and lot of literature is available worldwide. This paper examines presence of day of the month effect on eleven stock markets, geographically located in different corners of the world. This paper is not intended to study only the anomalies and inefficiencies present in various world markets, it is intended to highlight the profit potential available to individual investors and professional fund managers. The date wise daily returns are calculated in percentage terms to make the phenomena easy to understand. The statistical significance of daily returns is tested with ZStatistics, in total 341 hypotheses are tested in the research. To test the equality of returns on all days of a month we have used Kruskal-Wallis Test. We found day of the month effect present in all the stock markets tested across the world, some days in a month historically are found to have delivered significantly higher returns and there exists an opportunity to earn superior returns in the stock markets.

International Journal of Economics and Finance, 2015

The presence of asymmetries in stock returns, known as seasonal anomalies, has been rigorously probed in the array of academic literature evaluating the validity of Efficient Market Hypothesis. Even though there is an abundance of studies focusing on the presence of the day of the week effect, no clear-cut findings have been documented in both developed and emerging market stock exchanges. This paper attempts to investigate whether the day of the week effect exists on an initial dataset of 33 developed stock indices in the period between 1999 and 2013. However, the final dataset encompasses 24 indices belonging to 16 countries due to statistical considerations. The significant findings as to negative Monday and positive Friday returns belong to 3 and 6 of the indices, respectively. Whereas none of the markets demonstrates any significant Tuesday returns, only two of the markets show significantly negative Wednesday returns. Additionally, significant and positive Thursday returns are observed in 2 of the indices. Therefore, no systematic pattern has been detected as to the presence of the day of the week effect in selected developed stock indices during the period analyzed.

SSRN Electronic Journal, 2010

Efficient market stated that stock's return is indifferent in each trading day. But, the calendar effects phenomenon made a different return in each single day in a week or month. This is an abnormal return which can affect investor in deciding investment strategy, portfolio selection, and profit management. This study investigates the day of the week effect, more precisely the Monday effect and the January effect on the Stock Exchange of Mauritius (SEM) in order to get the information whether these anomalies exist or not. Linear regression model, GARCH and EGARCH models are used to answer our objective. The result shows that Monday effect is nonexistent in SEM. However, we find a significant positive January effect at market level. This study also concludes that volatility shocks are persistent in both daily and monthly returns and moreover, reports the presence of leverage effect in the daily stock returns.

Kelaniya Journal of Management, 2014

Many empirical studies have been carried out both in the developed and developing economies to test the presence of anomalies in stock returns and volatility. The most commonly tested seasonal anomalies are day of the week effect, month of the year effect, holiday effect, Monday effect and Friday effect. Previous studies strongly support the existence of seasonal anomalies. Existence of seasonal anomalies let the investors to earn abnormal returns by trading on past information. This study attempts to test whether the day of the week effect is present in the stock returns of the Colombo Stock Exchange. For this purpose, stock returns based on ASPI for the period of 2002 to 2011 with 2390 observation are taken into account. The day of the week effect hypothesis is tested using both OLS model and GARCH (1,1) model. The research provides strong evidence to support the day of the week effect. Furthermore, there is a Thursday, Wednesday and Friday effect in the stock returns. Thus, investors can earn abnormal returns by trading on a strategy based on past information. It is recommended to buy stock on Mondays and Tuesdays and sell them on Wednesdays, Thursdays and Fridays to earn abnormal returns.

The present study attempted to measure day-of-the-week effect on the returns and volatility of Bombay Stock Exchange (BSE) and National Stock Exchange (NSE) indices for the period from 2005 through 2014. Along with the descriptive statistics, t-test and ANOVA were used to capture mean deference in returns for the trading days Monday through Friday. Mean returns of only one index, Nifty Junior, were found statistically significant while using t-test ; whereas, no such difference was observed in any of the index (BSE and NSE) in ANOVA. To confirm the findings of t-test and ANOVA, an econometric model AR (1)-GARCH (1, 1) was used. In contrast to the findings of the other indices, returns on Monday for BSE small cap were found to be statistically significant. It was also observed that volatility on Monday for returns on BSE small cap were statistically significant. Returns on Tuesday, for BSE small cap and BSE mid cap, were found to be negative and statistically significant. Returns on these two indices were also found to be negatively volatile on Tuesday. Wednesday effect was only observed for Nifty Junior, but no volatility was captured on Wednesday for Nifty Junior. Returns on Nifty Junior were also found to be positive and statistically significant on Friday, but volatility was captured for returns on Nifty Junior on Friday.

2010

This paper investigates the existence of day-of-the-week effect for ten FTSE Bursa Malaysia indices. Standard procedure of determining calendar anomaly with additional GARCH related models are employed to determine the significance of the day-of-the-week effect. Results suggest that the day-of-the-week effect only exist for the FTSE Bursa Malaysia MESDAQ Index. However, the effect might be due to changing volatility since the negative and lowest Monday return does not appear to be significant in the EGARCH model. ABSTRAK Kajian ini mengkaji kewujudan kesan hari-dalam-minggu bagi sepuluh indeks FTSE Bursa Malaysia. Prosedur piawai bagi penentuan keganjilan kalendar beserta tambahan model berkaitan GARCH telah digunakan untuk menentukan kesignifikanan kesan hari-dalam-minggu. Hasil kajian mencadangkan bahawa kesan hari-dalamminggu hanya wujud bagi indeks MESDAQ FTSE Bursa Malaysia. Walau bagaimanapun, kesan tersebut mungkin disebabkan oleh perubahan kemeruapan kerana pulangan pada hari Isnin yang negatif dan terendah adalah ternayta tidak signifikan dalam model EGARCH.

European Journal of Business and Management, 2016

This study is an attempt to measure Day-of-the-Week Effect on the return and volatility of BSE and NSE indices for the period of 2005 through 2014. Along with the descriptive statistics, t-test and ANOVA has been used to capture mean deference in returns for the trading days Monday through Friday. Mean returns of only one index, Nifty Junior, has found statistically significant while using t-test whereas, no such difference was observed in any of the index (BSE and NSE) in ANOVA. To confirm the findings of t-test and ANOVA, an econometric model AR (1)-GARCH (1, 1) has been used. In contrast of the findings of the other indices, return on Monday for BSE Small Cap has found statistically significant. It has also observed that, volatility on Monday for return on BSE Small Cap is statistically significant. Return on Tuesday, for BSE Small Cap and BSE Mid Cap, has found negative and statistically significant. Returns on these two indices have also found negatively volatile on Tuesday. We...

This paper uses a data set from the FYROM Stock Exchange (MSE) to investigate whether the so – called calendar effects are present in this country over the period 3/1/2002 – 3/1/2007. Five calendar effects are examined in both mean by OLS regression and variance by GARCH [1,1]; the day of the week effect, the January effect, the half month effect, the turn of the month effect and the time of the month effect. In the empirical analysis, it was found that two of the tested calendar effects were present in the MSE (i.e. the monthly effect and the day of the Week effect) and that conclusions using Linear or GARCH methodology converged to similar results.

Review of Quantitative Finance and Accounting, 1996

This article employs daily closing index data to investigate the relationship between the U.S. and Japanese equity markets. It reassesses and extends the methodology over a longer sample space. The article then advances the analysis further by estimating structural equation models and by including the exchange rate as an additional explanatory variable. The resulting multivariate econometric design shows that the U.S. equity market strongly affects the Japanese equity market Monday through Friday while the Japanese market exerts a weaker influence on the U.S. market with the influence observed only on Mondays and Wednesdays. Key words: day-of-the-week effect, strucmraI equation models, linear structural relations (LISTREL) 294 R.A. MAYI, M.M. HADDAD AND L.E. TETRICK