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Volatility of BIST 100 Returns After 2020, Calendar Anomalies and COVID-19 Effect

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  • Ali CELÝK

Abstract

Market actors define the volatility in financial markets as a measure of risk. This study aims to investigate the volatility movements in the return series calculated on the closing values of the BIST 100 index between 01.Jan.2020-11.Feb.2021. In addition, the days of the week anomaly, the dates of public holiday, and COVID-19 pandemic effect were used as dummy variable in the econometric model. The findings showed that the EGARCH (3,3) model is to be the best performing model. Accordingly, Friday’s anomaly, Public Holidays, and the COVID-19 pandemic create negative shocks on the volatility movements of the return series, increase the volatility movements, and consequently, asymmetric and leverage effect emerged.

Suggested Citation

  • Ali CELÝK, 2021. "Volatility of BIST 100 Returns After 2020, Calendar Anomalies and COVID-19 Effect," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 15(1), pages 61-81.
    • Handle: RePEc:bdd:journl:v:15:y:2021:i:1:p:61-81
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    1. Cho, Young-Hyun & Linton, Oliver & Whang, Yoon-Jae, 2007. "Are there Monday effects in stock returns: A stochastic dominance approach," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 736-755, December.
    2. Berument, Hakan & Coskun, M. Nejat & Sahin, Afsin, 2007. "Day of the week effect on foreign exchange market volatility: Evidence from Turkey," Research in International Business and Finance, Elsevier, vol. 21(1), pages 87-97, January.
    3. Dima Alberg & Haim Shalit & Rami Yosef, 2008. "Estimating stock market volatility using asymmetric GARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 18(15), pages 1201-1208.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955, January.
    6. Frederic S. Mishkin, 1996. "Understanding Financial Crises: A Developing Country Perspective," NBER Working Papers 5600, National Bureau of Economic Research, Inc.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. St. Pierre, Eileen F., 1998. "Estimating EGARCH-M models: Science or art?," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(2), pages 167-180.
    9. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    10. H. Kent Baker & Abdul Rahman & Samir Saadi, 2008. "The day‐of‐the‐week effect and conditional volatility: Sensitivity of error distributional assumptions," Review of Financial Economics, John Wiley & Sons, vol. 17(4), pages 280-295, December.
    11. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    12. Hakan Berument & Halil Kiymaz, 2001. "The day of the week effect on stock market volatility," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 25(2), pages 181-193, June.
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    More about this item

    Keywords

    Volatility of BIST 100 returns; EGARCH; Calendar anomalies; COVID-19;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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