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The Application of GARCH and EGARCH in Modeling the Volatility of Daily Stock Returns During Massive Shocks: The Empirical Case of Egypt

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  • Ezzat, Hassan
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    Modeling volatility during a financial crisis where massive shocks are generated presents an ideal environment for investigating the dynamics of volatility during periods of extreme fluctuations for comparison with volatility during more tranquil periods. The objective of this paper is to study volatility of daily stock returns listed on the Egyptian Exchange during the political turmoil of 2011. The analysis is based on employing both GARCH and EGARCH models. Daily closing prices of four Egyptian stock market indices, the EGX 30, EGX70, EGX 100, and the EGX 20 capped were used in the analysis. The time frame was from the inception of each index to the 30th of June 2012. The sample period covers the period of pre-and post the Egyptian revolution which was shaped by extreme volatile fluctuations in stock returns. The EGARCH model was the method of choice for modeling the volatility in order to investigate the long memory and the leverage effect in the volatilities of the two periods. The findings reveal higher volatility during the revolution period for all indices reflected in higher standard deviations for both daily returns and absolute returns, with the EGX 70 displaying the highest volatility. The leverage effect was more apparent during the revolution period. However, long memory was more apparent during the pre-revolution period.

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    File URL: https://mpra.ub.uni-muenchen.de/50530/1/MPRA_paper_50530.pdf
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    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 50530.

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    Date of creation: Aug 2012
    Publication status: Published in International Research Journal of Finance and Economics 96 (2012): pp. 143-154
    Handle: RePEc:pra:mprapa:50530
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    8. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
    9. Brailsford, Timothy J. & Faff, Robert W., 1996. "An evaluation of volatility forecasting techniques," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 419-438, April.
    10. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    11. Mauro Mecagni & Maged Sawky Sourial, 1999. "The Egyptian Stock Market; Efficiency Tests and Volatility Effects," IMF Working Papers 99/48, International Monetary Fund.
    12. Tran MANH Tuyen, 2011. "Modeling Volatility Using GARCH Models: Evidence from Vietnam," Economics Bulletin, AccessEcon, vol. 31(3), pages 1935-1942.
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