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

Ibrahim, Omar (2019): Modelling Risk on the Egyptian Stock Market: Evidence from a Markov-Regime Switching GARCH Process.

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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.

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