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The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange

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  • Ezzat, Hassan
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    This paper examines sector specific volatility in order to determine how different sectors respond to volatility shocks within the same equity market. The Egyptian Exchange sector indices are used where firms are disaggregated and classified into twelve different sectors. Volatility is modeled using GARCH, EGARCH and TGARCH in order to examine the temporal volatility dynamics of each specific industry. Stylized facts such as volatility clustering, long memory and the leverage effect are investigated for each sector. Furthermore, the data is divided into two periods. The first period includes sector returns prior to the Egyptian revolution of January 25th 2011. This period was characterized by tranquil volatility. The second period includes the period of the revolution extending one and a half years after the revolution till June 30th 2012. This period was characterized by turbulent volatility. The findings indicate that TGARCH is the preferred model providing successful model specification for all sector indices during both periods. Although the stylized facts where apparent for most sectors for both periods, there was strong evidence of heterogeneous response of sector volatility due to the exogenous shocks of the revolution.

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    File URL: https://mpra.ub.uni-muenchen.de/51584/1/MPRA_paper_51584.pdf
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    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 51584.

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    Date of creation: 01 Dec 2012
    Publication status: Published in Journal of Money, Investment and Banking 27 (2013): pp. 68-85
    Handle: RePEc:pra:mprapa:51584
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    1. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España;Working Papers Homepage.
    2. CASTRO, Rui & CLEMENTI, Gian Luca & LEE, Yoonsoo, 2014. "Cross-sectoral variation in the volatility of plant-level idiosyncratic shocks," Cahiers de recherche 2014-09, Universite de Montreal, Departement de sciences economiques.
    3. Dimson, Elroy & Marsh, Paul, 1990. "Volatility forecasting without data-snooping," Journal of Banking & Finance, Elsevier, vol. 14(2-3), pages 399-421, August.
    4. Ezzat, Hassan, 2012. "The Application of GARCH and EGARCH in Modeling the Volatility of Daily Stock Returns During Massive Shocks: The Empirical Case of Egypt," MPRA Paper 50530, University Library of Munich, Germany.
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