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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

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.

Suggested Citation

  • Ezzat, Hassan, 2012. "The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange," MPRA Paper 51584, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:51584
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    File URL: https://mpra.ub.uni-muenchen.de/51584/1/MPRA_paper_51584.pdf
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    References listed on IDEAS

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    1. Rui Castro & Gian Luca Clementi & Yoonsoo Lee, 2015. "Cross Sectoral Variation in the Volatility of Plant Level Idiosyncratic Shocks," Journal of Industrial Economics, Wiley Blackwell, vol. 63(1), pages 1-29, March.
    2. Dimson, Elroy & Marsh, Paul, 1990. "Volatility forecasting without data-snooping," Journal of Banking & Finance, Elsevier, vol. 14(2-3), pages 399-421, August.
    3. 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.
    4. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España;Working Papers Homepage.
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    Cited by:

    1. Bahmani, Mohammad & Sheikh Ahmadi, Sayed Amir & Sanginabadi, Bahram, 2013. "Return Volatility and Asymmetric News of Computer Industry stocks in Tehran Stock Exchange (TEX)," MPRA Paper 70793, University Library of Munich, Germany, revised 15 Mar 2014.

    More about this item

    Keywords

    Egyptian Exchange; EGARCH; TGARCH; Idiosyncratic Risk; Revolution;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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