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Does Mood Explain the Monday Effect?

Author

Listed:
  • Michael H. Breitner
  • Christian Dunis
  • Hans-Jörg Mettenheim
  • Christopher Neely
  • Georgios Sermpinis
  • Azizah Abu Bakar
  • Antonios Siganos
  • Evangelos Vagenas‐Nanos

Abstract

ABSTRACT A number of studies have explored the sources of the Monday effect, according to which returns are on average negative on Mondays. We contribute to the literature by exploring whether a direct measure of mood explains the Monday effect. In line with psychological literature, a greater proportion of investors are more pessimistic in the early days of the week, and become more optimistic as the week progresses. We use novel daily mood data from Facebook across 20 international markets to explore the impact of mood on the Monday anomaly. We find that the Monday effect disappears after controlling for mood. In line with our hypothesis that mood drives the Monday effect, we find that the effect is more prominent within small capitalization indices and within collectivist and high‐uncertainty‐avoidance countries. Investors could consider mood levels to forecast Mondays with more (less) pronounced negative returns. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Azizah Abu Bakar & Antonios Siganos & Evangelos Vagenas‐Nanos, 2014. "Does Mood Explain the Monday Effect?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 409-418, September.
    • Handle: RePEc:wly:jforec:v:33:y:2014:i:6:p:409-418
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    Cited by:

    1. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    2. Umara Noreen & Attayah Shafique & Usman Ayub & Syed Kashif Saeed, 2022. "Does the Adaptive Market Hypothesis Reconcile the Behavioral Finance and the Efficient Market Hypothesis?," Risks, MDPI, vol. 10(9), pages 1-14, August.
    3. Ausloos, Marcel & Nedic, Olgica & Dekanski, Aleksandar & Mrowinski, Maciej J. & Fronczak, Piotr & Fronczak, Agata, 2017. "Day of the week effect in paper submission/acceptance/rejection to/in/by peer review journals. II. An ARCH econometric-like modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 462-474.
    4. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    5. Sakhr Miss & Michel Charifzadeh & Tim A. Herberger, 2020. "Revisiting the monday effect: a replication study for the German stock market," Management Review Quarterly, Springer, vol. 70(2), pages 257-273, May.
    6. Ali, Fahad & Ülkü, Numan, 2020. "Weekday seasonality of stock returns: The contrary case of China," Journal of Asian Economics, Elsevier, vol. 68(C).
    7. Gavriilidis, Konstantinos & Kallinterakis, Vasileios & Tsalavoutas, Ioannis, 2016. "Investor mood, herding and the Ramadan effect," Journal of Economic Behavior & Organization, Elsevier, vol. 132(S), pages 23-38.
    8. Yılmaz, Emrah Sıtkı & Ozpolat, Aslı & Destek, Mehmet Akif, 2022. "Do Twitter Sentiments Really Effective on Energy Stocks? Evidence from Intercompany Dependency," MPRA Paper 114155, University Library of Munich, Germany.
    9. Shanaev, Savva & Shuraeva, Arina & Fedorova, Svetlana, 2022. "The Groundhog Day stock market anomaly," Finance Research Letters, Elsevier, vol. 47(PA).
    10. Autore, Don M. & Jiang, Danling, 2019. "The preholiday corporate announcement effect," Journal of Financial Markets, Elsevier, vol. 45(C), pages 61-82.
    11. Liu, Tianhao, 2021. "A study on day-of-week effect of submission: Based on the data of JSFST," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    12. Patrick Houlihan & Germán G. Creamer, 2017. "Can Sentiment Analysis and Options Volume Anticipate Future Returns?," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 669-685, December.
    13. Richards, Daniel W. & Willows, Gizelle D., 2018. "Who trades profusely? The characteristics of individual investors who trade frequently," Global Finance Journal, Elsevier, vol. 35(C), pages 1-11.
    14. Liang Meng & Haifeng Wang & Pengfei Han, 2020. "Getting a head start: turn-of-the-month submission effect for accepted papers in management journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2577-2595, September.
    15. Richards, Daniel W. & Willows, Gizelle D., 2019. "Monday mornings: Individual investor trading on days of the week and times within a day," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 105-115.
    16. Yuliang Yao & Martin Dresner & Kevin Xiaoguo Zhu, 2019. "“Monday Effect” on Performance Variations in Supply Chain Fulfillment: How Information Technology–Enabled Procurement May Help," Information Systems Research, INFORMS, vol. 30(4), pages 1402-1423, December.
    17. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of Twitter sentiment on renewable energy stocks," Energy Economics, Elsevier, vol. 76(C), pages 153-169.
    18. Ausloos, Marcel & Nedic, Olgica & Dekanski, Aleksandar, 2016. "Day of the week effect in paper submission/acceptance/rejection to/in/by peer review journals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 197-203.

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