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Measuring Extreme Market Risk: The Sri Lankan Context

Author

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  • Wijeyakulasuriya D. A.

    (Department of Statistics, University of Colombo, P. O. Box 1490, Colombo, Sri Lanka)

  • Wickremasinghe W. N.

    (Department of Statistics, University of Colombo, P. O. Box 1490, Colombo, Sri Lanka)

Abstract

Many empirical studies have been carried out in developed and emerging markets using methods to account for extreme market risk. A front-runner in the methods used is Extreme Value Theory (EVT). In this study, these methods are applied to the All Share Price Index (ASPI) of the Colombo Stock Exchange (CSE) to obtain risk forecasts for VaR (Value at Risk) and ES (Expected Shortfall) at 99% confidence level. Recognizing the merits of both conditional and unconditional models for risk measures the most suitable unconditional model and conditional model are found for the ASPI. Contrary to other studies the Historical Simulation method was found to be more appropriate for obtaining static estimates than the static EVT model. The Two-Step Approach of McNeil and Frey which combines EVT and Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) methodologies was found to be the most appropriate conditional model. Backtesting of models is done using a binomial test, Christoferssen’s conditional coverage test and McNeil and Frey’s ES test.

Suggested Citation

  • Wijeyakulasuriya D. A. & Wickremasinghe W. N., 2015. "Measuring Extreme Market Risk: The Sri Lankan Context," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(2), pages 185-201, July.
    • Handle: RePEc:bpj:apjrin:v:9:y:2015:i:2:p:185-201:n:3
    DOI: 10.1515/apjri-2014-0026
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    References listed on IDEAS

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    1. Degiannakis, Stavros & Floros, Christos & Livada, Alexandra, 2012. "Evaluating Value-at-Risk Models before and after the Financial Crisis of 2008: International Evidence," MPRA Paper 80463, University Library of Munich, Germany.
    2. Gencay, Ramazan & Selcuk, Faruk, 2004. "Extreme value theory and Value-at-Risk: Relative performance in emerging markets," International Journal of Forecasting, Elsevier, vol. 20(2), pages 287-303.
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