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Calendar Anomalies in the Ukrainian Stock Market

Author

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  • Guglielmo Maria Caporale
  • Alex Plastun

Abstract

This paper is a comprehensive investigation of calendar anomalies in the Ukrainian stock market. It employs various statistical techniques (average analysis, Student's t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) and a trading simulation approach to test for the presence of the following anomalies: Day of the Week Effect; Turn of the Month Effect; Turn of the Year Effect; Month of the Year Effect; January Effect; Holiday Effect; HalloweenEffect. The results suggest that in general calendar anomalies are not present in the Ukrainian stock market, but there are a few exceptions, i.e. the Turn of the Year and Halloween Effect for the PFTS index, and the Month of the Year Effect for UX futures. However, the trading simulation analysis shows that only trading strategies based on the Turn of the Year Effect for the PFTS index and the Month of the Year Effect for the UX futures can generate exploitable profit opportunities that can be interpreted as evidence against market efficiency.

Suggested Citation

  • Guglielmo Maria Caporale & Alex Plastun, 2016. "Calendar Anomalies in the Ukrainian Stock Market," Discussion Papers of DIW Berlin 1573, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1573
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    References listed on IDEAS

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    1. Schwert, G. William, 2003. "Anomalies and market efficiency," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 15, pages 939-974, Elsevier.
    2. Rozeff, Michael S. & Kinney, William Jr., 1976. "Capital market seasonality: The case of stock returns," Journal of Financial Economics, Elsevier, vol. 3(4), pages 379-402, October.
    3. Wing-Keung Wong & Aman Agarwal & Nee-Tat Wong, 2006. "The Disappearing Calendar Anomalies in the Singapore Stock Market," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 11(2), pages 123-139, Jul-Dec.
    4. 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.
    5. Guglielmo Maria Caporale & Luis A. Gil-Alana & Alex Plastun & Inna Makarenko, 2014. "The Weekend Effect: A Trading Robot and Fractional Integration Analysis," CESifo Working Paper Series 4849, CESifo.
    6. Ariel, Robert A, 1990. "High Stock Returns before Holidays: Existence and Evidence on Possible Causes," Journal of Finance, American Finance Association, vol. 45(5), pages 1611-1626, December.
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    13. 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.
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    Cited by:

    1. Caporale, Guglielmo Maria & Plastun, Alex, 2019. "The day of the week effect in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 31(C).
    2. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    3. Peter Arendas & Jana Kotlebova, 2019. "The Turn of the Month Effect on CEE Stock Markets," IJFS, MDPI, vol. 7(4), pages 1-19, October.

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    More about this item

    Keywords

    Calendar anomalies; day of the week effect; turn of the month effect; month of the year effect; january effect; holiday effect; halloween effect;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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