A Bootstrap Method to Calculate Value-At-Risk in Emerging Markets under Stochastic Volatility Models

Cheng-Der Fuh ； Yu-Lin Yang

《中國統計學報》 45卷2期 (2007/06) Pp. 106-129

https://doi.org/10.29973/JCSA.200706.0001

並列摘要

These days, risk management is an important issue. A standard benchmark used to measure and to manage market risks is the Value-at-Risk (VaR). Since emerging markets have drawn considerable interest in recent years, this article applies the bootstrap method to calculate the VaR estimate of nine emerging market stock indices. We also examine the US S&P 500 composite index and MSCI EM (Emerging Markets) Index for comparison. Simulation results show that the VaR estimate is not far from the true VaR. A back-test shows that stochastic volatility models with ε~N(0, 1) or ~t(6) or ~t(4) can fit the different indices examined in this article. The VaR estimates are relatively high in Turkey, India, Mexico, Russia and Indonesia; while Thailand, Korea, Taiwan and Malaysia have relatively low VaR estimates. As we expect, the S&P 500 index has a relatively low VaR estimate. However, the fact that the MSCI EM Index has a relatively high VaR estimate indicates that the diversification effects are not significant between emerging markets.

並列關鍵字

Bootstrap ； emerging markets ； Value-at-Risk ； stochastic volatility ； EM algorithm

參考文獻

Allen, M.(1994).Building a Role Model.Risk.7,73-80.

Bao, Y.,T. H. Lee,B. Saltoglu(2006).Evaluating Predictive Performance of Value-at-Risk Models in Emerging Markets: A Reality Check.Journal of Forecasting.25,101-128.

Beder, T.(1995).VaR: Seductive but Dangerous.Financial Analysts Journal.51,12-24.

Bekaert, G.,C. R. Harvey(1997).Emerging Equity Market Volatility.Journal of Financial Economics.43,29-77.

Cappé, O.,E. Moulines,T. Rydén(2005).Inference in Hidden Markov Models.Springer.