Value at Risk and Conditional Extreme Value Theory via Markov Regime Switching Models

Ze-To, S. 2008. Value at Risk and Conditional Extreme Value Theory via Markov Regime Switching Models. Journal of Futures Markets. 28 (2), pp. 155-181. https://doi.org/10.1002/fut.20293

TitleValue at Risk and Conditional Extreme Value Theory via Markov Regime Switching Models
TypeJournal article
AuthorsZe-To, S.
Abstract

This study develops a new conditional extreme value theory-based (EVT) model that incorporates the Markov regime switching process to forecast extreme risks in the stock markets. The study combines the Markov switching ARCH (SWARCH) model (which uses different sets of parameters for various states to cope with the structural changes for measuring the time-varying volatility of the return distribution) with the EVT to model the tail distribution of the SWARCH processed residuals. The model is compared with unconditional EVT and conditional EVT-GARCH models to estimate the extreme losses in three leading stock indices: S&P 500 Index, Hang Seng Index and Hang Seng China Enterprise Index. The study found that the EVT-SWARCH model outperformed both the GARCH and SWARCH models in capturing the non-normality and in providing accurate value-at-risk forecasts in the in-sample and out-sample tests. The EVTSWARCH model, which exhibits the features of measuring the volatility of a heteroscedastic financial return series and coping with the non-normality owing to structural changes, can be an alternative measure of the tail risk.

KeywordsValue at Risk
EVT
SWARCH model
JournalJournal of Futures Markets
Journal citation28 (2), pp. 155-181
ISSN1096-9934
Year2008
PublisherWiley
Digital Object Identifier (DOI)https://doi.org/10.1002/fut.20293
Publication dates
PublishedFeb 2008

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