Semi-monthly effect in stock returns: new evidence from Bombay Stock Exchange

  • Received June 13, 2017;
    Accepted September 14, 2017;
    Published October 25, 2017
  • Author(s)
    Shakila B. ,
    Prakash Pinto
    ORCID ,
    E-mail:
    Iqbal Thonse Hawaldar
    ORCID Researcher ID
  • DOI
    http://dx.doi.org/10.21511/imfi.14(3-1).2017.01
  • Article Info
    Volume 14 2017, Issue #3, pp. 160-172
  • TO CITE АНОТАЦІЯ
  • Cited by
    8 articles
  • 2627 Views
  • 776 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Semi-monthly effect is a kind of calendar anomalies which is less explored in the financial literature. The main objective of this paper to investigate the presence of semi-monthly effect in selected sectoral indices of Bombay Stock Exchange (BSE). The study uses the daily stock returns of five sectoral indices viz S&P BSE Auto Index, S&P BSE Bankex, S&P BSE Consumer Durables Index, S&P BSE FMCG Index and S&P BSE Health Care Index for the period of 10 years starting from 1st April 2007 to 31st March 2017. The data were analyzed using two approaches namely calendar days approach and trading days approach. To test the equality of mean returns for the two halves of the month, Mann-Whitney U test is used. The empirical results of the study did not provide any evidence for the presence of semi-monthly effect in the selected sectoral indices. Nevertheless, BSE Auto Index showed significant difference in the mean returns of first half and second half of trading month during the study period.

view full abstract hide full abstract
    • Table 1. Results of descriptive statistics for the first half of the calendar month and second half of the calendar month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE Auto Index from April 2007 to March 2017
    • Table 2. Results of descriptive statistics for the first half of the calendar month and second half of the calendar month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE BANKEX from April 2007 to March 2017
    • Table 3. Results of descriptive statistics for the first half of the calendar month and second half of the calendar month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE Consumer Durables Index from April 2007 to March 2017
    • Table 4. Results of descriptive statistics for the first half of the calendar month and second half of the calendar month and Mann-Whitney U (Z-score) for the difference of these Two Means of S&P BSE FMCG Index from April 2007 to March 2017
    • Table 5. Results of descriptive statistics for the first half of the calendar month and second half of the calendar month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE Health Care Index from April 2007 to March 2017
    • Table 6. Results of descriptive statistics for the first half of the trading month and second half of the trading month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE AUTO from April 2007 to March 2017
    • Table 7. Results of descriptive statistics for the first half of the trading month and second half of the trading month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE BANKEX from April 2007 to March 2017
    • Table 8. Results of descriptive statistics for the first half of the trading month and second half of the trading month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE Consumer Durables from April 2007 to March 2017
    • Table 9. Results of descriptive statistics for the first half of the trading month and second half of the trading month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE FMCG Index from April 2007 to March 2017
    • Table 10. Results of descriptive statistics for the first half of the trading month and second half of the trading month and Mann-Whitney U (Z-score) for the difference of these two means of S&P BSE Health Care Index from April 2007 to March 2017
Related Articles

  • Calendar anomalies in the Ukrainian stock market

    Guglielmo Maria Caporale , Alex PlastunORCID Researcher ID doi: http://dx.doi.org/10.21511/imfi.14(1).2017.11
    Investment Management and Financial Innovations Volume 14, 2017         Issue #1         pp. 104-114 Views: 1617 Downloads: 398 TO CITE АНОТАЦІЯ

    This paper is a comprehensive investigation of calendar anomalies in the Ukrainian stock market. It employs various statistical techniques (average analysis, Student’s t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) and a trading simulation approach to test for the presence of the following anomalies: day-of-the-week effect; turn-of-the-month effect; turn-of-the-year effect; month-of-the-year effect; January effect; holiday effect; Halloween effect. The results suggest that in general calendar anomalies are not present in the Ukrainian stock market, but there are a few exceptions, i.e. the turn-of-the-year and Halloween effect for the PFTS index, and the month-of-the-year effect for UX futures. However, the trading simulation analysis shows that only trading strategies based on the turn-of-the-year effect for the PFTS index and the month-of-the-year effect for the UX futures can generate exploitable profit opportunities that can be interpreted as evidence against market efficiency.

  • The January barometer in emerging markets: new evidence from the Gulf Cooperation Council stock exchanges

    Costas SiriopoulosORCID , Layal Youssef doi: http://dx.doi.org/10.21511/imfi.16(4).2019.06
    Investment Management and Financial Innovations Volume 16, 2019         Issue #4         pp. 61-71 Views: 1081 Downloads: 139 TO CITE АНОТАЦІЯ

    International investors’ interest in the capital markets in the region of Gulf countries has dramatically increased in last two decades. Thus, it would be motivating to investigate their characteristics, where the January anomaly is a major one. This paper studies the veracity of the January effect rule in the Gulf Cooperation Council (GCC) stock markets and examines the predictive power of January returns. Seven GCC stock markets are tested – the market indices in Bahrain, Abu Dhabi, Dubai, Kuwait, Oman, Qatar, and Saudi Arabia – from January 1, 2001 until December 31, 2018, a timeframe which has rarely been analyzed. Ordinary least square (OLS)-based dummy variable regression equation was used as the conventional econometric procedure in the works of financial calendar anomalies in stock markets. Some evidence is reported for the markets of Dubai and Kuwait. The paper also provides an additional explanation for the performance of stock market of Kuwait. The findings are opposite to the well documented evidence that emerging markets are less efficient and hence it is likely that several market anomalies are further pronounced. The results suggest that the predictive power of the January anomaly can be considered as a temporary anomaly in the GCC markets, since it is concentrated in only a couple of GCC markets and does not persist in time.

Download Preview
Close
Investment Management and Financial Innovations
Investment Management and Financial Innovations