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The January effect across volatility regimes

Author

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  • 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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    References listed on IDEAS

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    1. Chien, Chin-Chen & Lee, Cheng-few & Wang, Andrew M. L., 2002. "A note on stock market seasonality: The impact of stock price volatility on the application of dummy variable regression model," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(1), pages 155-162.
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    3. Al-Khazali, Osamah M., 2001. "Does the January effect exist in high-yield bond market?," Review of Financial Economics, Elsevier, vol. 10(1), pages 71-80.
    4. Lean, Hooi Hooi & Smyth, Russell & Wong, Wing-Keung, 2007. "Revisiting calendar anomalies in Asian stock markets using a stochastic dominance approach," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 125-141, April.
    5. Fama, Eugene F & French, Kenneth R, 1996. " Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    6. Bing Zhang & Xindan Li, 2006. "Do Calendar Effects Still Exist in the Chinese Stock Markets?," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 4(2), pages 151-163.
    7. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    8. Dimitar Tonchev & Tae-Hwan Kim, 2004. "Calendar effects in Eastern European financial markets: evidence from the Czech Republic, Slovakia and Slovenia," Applied Financial Economics, Taylor & Francis Journals, vol. 14(14), pages 1035-1043.
    9. Laura T. Starks & Li Yong & Lu Zheng, 2006. "Tax-Loss Selling and the January Effect: Evidence from Municipal Bond Closed-End Funds," Journal of Finance, American Finance Association, vol. 61(6), pages 3049-3067, December.
    10. Keim, Donald B., 1983. "Size-related anomalies and stock return seasonality : Further empirical evidence," Journal of Financial Economics, Elsevier, vol. 12(1), pages 13-32, June.
    11. Cooper, Michael J. & McConnell, John J. & Ovtchinnikov, Alexei V., 2006. "The other January effect," Journal of Financial Economics, Elsevier, vol. 82(2), pages 315-341, November.
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    Cited by:

    1. Floros, Christos & Salvador, Enrique, 2014. "Calendar anomalies in cash and stock index futures: International evidence," Economic Modelling, Elsevier, vol. 37(C), pages 216-223.
    2. Kumar, Satish, 2016. "Revisiting calendar anomalies: Three decades of multicurrency evidence," Journal of Economics and Business, Elsevier, vol. 86(C), pages 16-32.
    3. repec:blg:journl:v:12:y:2017:i:1:p:95-109 is not listed on IDEAS

    More about this item

    Keywords

    Markov switching model; Stock returns; Seasonality; Size portfolios;

    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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