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The January effect across volatility regimes

Author

Listed:
  • Betty Agnani
  • Henry Aray

Abstract

Using a Markov regime switching model, this article presents evidence of the well-known January effect on stock returns. The specification allows a distinction to be drawn between two regimes: one with high volatility and another with low volatility. We obtain a time-varying January effect that is, in general, positive and significant in both volatility regimes. However, this effect is larger in the high-volatility regime. In sharp contrast with most of the previous literature, we find two major results: (1) the January effect exists for all sizes of portfolio; (2) the negative correlation between the magnitude of the January effect and portfolio size fails across volatility regimes. Moreover, our evidence supports a slight decline in the January effect for all sizes of portfolio except the smallest, for which it is even larger.

Suggested Citation

  • Betty Agnani & Henry Aray, 2011. "The January effect across volatility regimes," Quantitative Finance, Taylor & Francis Journals, vol. 11(6), pages 947-953.
    • Handle: RePEc:taf:quantf:v:11:y:2011:i:6:p:947-953
    DOI: 10.1080/14697680903540373
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    Cited by:

    1. Mai, Nhat Chi, 2014. "Monetary transmission mechanism analysis in a small, open economy: the case of Vietnam," OSF Preprints ybc8p, Center for Open Science.
    2. Obalade Adefemi A. & Muzindutsi Paul-Francois, 2019. "Calendar Anomalies, Market Regimes, and the Adaptive Market Hypothesis in African Stock Markets," Journal of Management and Business Administration. Central Europe, Sciendo, vol. 27(4), pages 71-94, December.
    3. Floros, Christos & Salvador, Enrique, 2014. "Calendar anomalies in cash and stock index futures: International evidence," Economic Modelling, Elsevier, vol. 37(C), pages 216-223.
    4. Girardin, Eric & Salimi Namin, Fatemeh, 2019. "The January effect in the foreign exchange market: Evidence for seasonal equity carry trades," Economic Modelling, Elsevier, vol. 81(C), pages 422-439.
    5. KUMAR Satish, 2017. "A Review On The Evolution Of Calendar Anomalies," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 12(1), pages 95-109, April.
    6. Leković Miljan, 2018. "Evidence for and Against the Validity of Efficient Market Hypothesis," Economic Themes, Sciendo, vol. 56(3), pages 369-387, September.
    7. Kumar, Satish, 2016. "Revisiting calendar anomalies: Three decades of multicurrency evidence," Journal of Economics and Business, Elsevier, vol. 86(C), pages 16-32.

    More about this item

    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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