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Are stock returns different over weekends? a jump diffusion analysis of the \"weekend effect\"

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  • Peter Fortune

Abstract

The distribution of returns on common stocks is, arguably, one of the most widely studied financial market characteristics. The performance of stock prices during breaks in trading has received considerable attention in recent years, especially since the advent of \"circuit breakers\" designed to create stability when markets are chaotic. This study examines the distribution of daily returns on five popular stock price indices, with a special emphasis on the difference between returns over weekends and returns over adjacent intraweek trading days. The author revisits the \"weekend effect\" in common stock returns, focusing on two characteristics of differential returns over intraweek trading days and over weekends: the \"drift\" and the \"volatility.\" He finds that the volatility of stock returns over weekends is much smaller than could be predicted from intraweek volatility. This is true of stock returns over weekends both before and after October 1987. He also finds that the difference between intraweek drift and weekend drift is smaller after October 1987 than before. Indeed, it disappears for large companies, suggesting that the poor performance of common stocks over weekends in the 1980s was a financial anomaly that was mitigated over time, as investors incorporated it into the timing of their transactions. The sharp decrease in volatility over weekends is consistent with the view that active trading actually increases volatility, so that a close in trading will be consistent with a reduction in volatility. However, a weekend is a scheduled event, which might simply reduce the rate of new information flow, while a sudden halt in trading might eliminate all information flow from price discovery, creating an environment that elicits the volatility it is designed to mitigate.

Suggested Citation

  • Peter Fortune, 1999. "Are stock returns different over weekends? a jump diffusion analysis of the \"weekend effect\"," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 3-19.
  • Handle: RePEc:fip:fedbne:y:1999:i:sep:p:3-19
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    1. Rudel, Richard K. & McCamley, Francis P., 2000. "Volatility Of Cash Corn Prices By Day-Of-The-Week," 2000 Annual meeting, July 30-August 2, Tampa, FL 21873, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. B Harrison & D Paton, 2007. "Do fat tails matter in GARCH estimation: testing market efficiency in two transition economies," Economic Issues Journal Articles, Economic Issues, vol. 12(2), pages 15-26, September.
    3. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana & Alex Plastun, 2016. "The weekend effect: an exploitable anomaly in the Ukrainian stock market?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 43(6), pages 954-965, November.
    4. Hsiang-Hsi Liu & Yu-Cheng Lin, 2021. "Relationships among US S&P500 Stock Index, its Futures and NASDAQ Index Futures with Volatility Spillover and Jump Diffusion: Modeling and Hedging Performance," Bulletin of Applied Economics, Risk Market Journals, vol. 8(1), pages 121-148.
    5. Peter Fortune, 2003. "Margin requirements across equity-related instruments: how level is the playing field?," New England Economic Review, Federal Reserve Bank of Boston, pages 31-50.
    6. Zhang, Lei & Chen, Yan & Bouri, Elie, 2024. "Time-varying jump intensity and volatility forecasting of crude oil returns," Energy Economics, Elsevier, vol. 129(C).
    7. Barry Harrison & David Paton, 2004. "Do ‘Fat Tails’ Matter in GARCH Estimation? Stock Market Efficiency in Romania and the Czech Republic," Working Papers 2004/3, Nottingham Trent University, Nottingham Business School, Economics Division.
    8. Plastun, Alex & Sibande, Xolani & Gupta, Rangan & Wohar, Mark E., 2020. "Price gap anomaly in the US stock market: The whole story," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    9. Peter Fortune, 2001. "Margin lending and stock market volatility," New England Economic Review, Federal Reserve Bank of Boston, pages 3-25.
    10. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun & Inna Makarenko, 2014. "The Weekend Effect: A Trading Robot and Fractional Integration Analysis," Discussion Papers of DIW Berlin 1386, DIW Berlin, German Institute for Economic Research.
    11. Barry Harrison & David Paton, 2005. "Transition, the Evolution of Stock Market Efficiency and Entry into EU: The Case of Romania," Economic Change and Restructuring, Springer, vol. 37(3), pages 203-223, September.
    12. Miguel Balbina, 2002. "The Analysis of Seasonal Return Anomalies in the Portuguese Stock Market," Working Papers w200211, Banco de Portugal, Economics and Research Department.
    13. Andreas Georgantopoulos & Anastasios Tsamis, 2011. "Investigating Seasonal Patterns in Developing Countries: The Case of FYROM Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 1(4), pages 211-219.
    14. Guglielmo Maria Caporale & Alex Plastun, 2016. "Calendar Anomalies in the Ukrainian Stock Market," CESifo Working Paper Series 5877, CESifo.
    15. Ralph C. Kimball, 2000. "Failures in risk management," New England Economic Review, Federal Reserve Bank of Boston, issue Jan, pages 3-12.
    16. Lundgren, Jens & Hellström, Jörgen & Rudholm, Niklas, 2008. "Multinational Electricity Market Integration and Electricity Price Dynamics," HUI Working Papers 16, HUI Research.
    17. Jeong, Daehee & Kim, Hwagyun & Park, Joon Y., 2015. "Does ambiguity matter? Estimating asset pricing models with a multiple-priors recursive utility," Journal of Financial Economics, Elsevier, vol. 115(2), pages 361-382.
    18. Zainal Abidin, Shahida Nadia & Wan Mahmood, Wan Mansor, 2007. "Day-of-the-Week Effect on the Bursa (Bourse) Malaysia: Further Evidence from Robust Estimations," MPRA Paper 13326, University Library of Munich, Germany.
    19. Anthony Gu, 2004. "The Reversing Weekend Effect: Evidence from the U.S. Equity Markets," Review of Quantitative Finance and Accounting, Springer, vol. 22(1), pages 5-14, January.

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