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Turn‐of‐the‐month and intramonth effects: Explanation from the important macroeconomic news announcements

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  • Jussi Nikkinen
  • Petri Sahlström
  • Janne Äijö

Abstract

This study provides a new and economically plausible explanation for turn‐of‐the‐month and intramonth anomalies. It is suggested that these anomalies arise from clustered information, namely from important macroeconomic news announcements, which are released systematically at a certain point each month. It is verified that both anomalies exist in SP100 returns. However, once the effect of macroeconomic news announcements has been taken into account, these anomalies disappear. A measure is proposed which uses information from option‐implied volatilities to account for the changes in expected risk premium caused by news announcements. This measure is found to capture incompletely the effects of news announcements, which may due to the misreactions observed on the options market or alternative explanations, such as increased liquidity or investors' overreaction resulting in higher realized returns. Consequently, the underlying mechanism remains to some extent inconclusive although the empirical results provide strong support for the macroeconomic news announcement hypothesis. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:105–126, 2007

Suggested Citation

  • Jussi Nikkinen & Petri Sahlström & Janne Äijö, 2007. "Turn‐of‐the‐month and intramonth effects: Explanation from the important macroeconomic news announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(2), pages 105-126, February.
    • Handle: RePEc:wly:jfutmk:v:27:y:2007:i:2:p:105-126
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    Cited by:

    1. Eleftherios Giovanis, 2014. "The Turn-of-the-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 7(3), pages 43-61, December.
    2. Jasiński, Tomasz, 2022. "A new approach to modeling cycles with summer and winter demand peaks as input variables for deep neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    3. Krieger, Kevin & Mauck, Nathan & Vazquez, Joseph, 2015. "Comparing U.S. and European market volatility responses to interest rate policy announcements," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 127-136.
    4. Nikkinen, Jussi & Rothovius, Timo, 2019. "Market specific seasonal trading behavior in NASDAQ OMX electricity options," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 16-29.
    5. Elena Valentina Tilica, 2018. "Turn-of-the-month and day-of-the-week patterns: two for the price of one? The Romanian situation," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 10(1), pages 047-058, June.
    6. Tariq Aziz & Valeed Ahmad Ansari, 2018. "The Turn of the Month Effect in Asia-Pacific Markets: New Evidence," Global Business Review, International Management Institute, vol. 19(1), pages 214-226, February.
    7. Michael Weigerding & Michael Hanke, 2018. "Drivers of seasonal return patterns in German stocks," Business Research, Springer;German Academic Association for Business Research, vol. 11(1), pages 173-196, February.

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