Quian Cheng, David E. Giles, Hui Feng
Extreme Value Theory (EVT) measures the behaviour of extreme observations on a random variable. EVT in risk management, an approach to modelling and measuring risks under rare events, has taken on a prominent role in recent years. This article contributes to the literature in two respects by analysing an interesting international financial data set. First, we apply conditional EVT to examine the Value at Risk (VaR) and the Expected Shortfall (ES) for the Chinese and several representative international stock market indices: Hang Seng (Hong Kong), TSEC (Taiwan), Nikkei 225 (Japan), Kospi (Korea), BSE (India), STI (Singapore), S&P 500 (US), SPTSE (Canada), IPC (Mexico), CAC 40 (France), DAX 30 (Germany), FTSE100 (UK) index. We find that China has the highest VaR and ES for negative daily stock returns. Second, we examine the extreme dependence between these stock markets, and we find that the Chinese market is asymptotically independent of the other stock markets considered.
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