The interrelation of stock markets in China, Taiwan and Hong Kong and their constructional portfolio’s value-at-risk estimate

ABSTRACT This study employs a bivariate asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) model to estimate the return, variance and covariance for three stock-based portfolios composed of two alternative indexes of the stock markets in China, Hong Kong and Taiwan, explores the return and volatility spillover effects between two indexes of the portfolio constructed and estimates the out-of-sample value-at-risk (VaR). Using the effective validation framework proposed by the Board of Governors of the US Federal Reserve System, this study finds that, as shown in the price levels and spillover effects on return and volatility, the stock markets in these three regions are closely related and are significantly positively correlated. Moreover, there is a volatility feedback effect in China's stock market and a significant leverage effect in the Hong Kong and Taiwan stock markets. Furthermore, via the construction of portfolios, market risk can be reduced and the stock-based portfolio, which is composed of stock indexes in China and Taiwan, has the optimal risk dispersion. Finally, from the performance competition of alternative VaR models, two semiparametric approaches, weighted historical simulation (WHS) and, in particular, filtered historical simulation (FHS), can reduce the underestimation of the true risk caused by an inappropriate return distribution setting of the parametric approach. Moreover, the effects of this approach are more influential than the leverage effect on the VaR estimates. Hence, the FHS approach with the asymmetric volatility specification model, FHS-B-JR, is optimal, enabling precise forecasting of theVaR. In addition, regarding the backtesting, the loss functions are more sensitive than the accuracy measure tests.