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Modelling Risk on the Egyptian Stock Market: Evidence from a Markov-Regime Switching GARCH Process

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  • Ibrahim, Omar

Abstract

This research aims at evaluating among market risk measures to equity exposures on the Egyptian stock market, while utilising a variety of parametric and non-parametric methods to estimating volatility dynamics. Historical Simulation, EWMA (RiskMetrics), GARCH, GJR-GARCH, and Markov-Regime switching GARCH models are empirically estimated. Value at Risk and Conditional Value at Risk measures are backtested in order to evaluate among the alternative models. Results indicate the superiority of asymmetric GARCH models when combined with a Markov-Regime switching process in quantifying market risk - as is evident from the results of the backtests - which have been performed in accordance with the current regulatory demands. Implications are important to regulators and practitioners.

Suggested Citation

  • Ibrahim, Omar, 2019. "Modelling Risk on the Egyptian Stock Market: Evidence from a Markov-Regime Switching GARCH Process," MPRA Paper 98091, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:98091
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    Cited by:

    1. Ibrahim, Omar, 2021. "Measuring the Output Effects of Fiscal Policy in Egypt: A Disaggregated Structural VAR Analysis," MPRA Paper 110962, University Library of Munich, Germany.

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    More about this item

    Keywords

    Risk Management; Value at Risk; GARCH; Markov Chains;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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