Ezzat, Hassan (2012): The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange. Published in: Journal of Money, Investment and Banking No. 27 (March 2013): pp. 6885.

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Abstract
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.
Item Type:  MPRA Paper 

Original Title:  The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange 
Language:  English 
Keywords:  Egyptian Exchange, EGARCH, TGARCH, Idiosyncratic Risk, Revolution 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C14  Semiparametric and Nonparametric Methods: General C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C32  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics D  Microeconomics > D5  General Equilibrium and Disequilibrium > D53  Financial Markets G  Financial Economics > G1  General Financial Markets > G17  Financial Forecasting and Simulation 
Item ID:  51584 
Depositing User:  Dr. Hassan Ezzat 
Date Deposited:  25 Nov 2013 04:47 
Last Modified:  27 Sep 2019 05:07 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/51584 