dc.description.abstract | Financial Crisis and Risk Spillover: An Application of the DCC Model
In this paper, we apply the Dynamic Conditional Correlation Multivariate GARCH (DCC MV-GARCH) model, proposed by Engle (2001), to investigate the effects of risk-spillover between currency and equity markets during the Asian crisis. We consider seven Asian countries including ndonesia, Japan, Malaysia, Philippines, South Korea, Taiwan, and Thailand.
The Asian crisis began in July 1997 with the devaluation of the Thai baht and it spread out quickly through East Asia. Although each country experienced the crisis with differing intensity and duration, eventually the global economy is affected by this crisis and causing several emerging countries experience deep recessions.
Many economists have evaluted the relationships among international financial markets and also the intermarket dependencies within each country since the Asian crisis. Studies of Asian crisis mostly focus on the first moment (return), however, volatility (the second moment) plays a key role in many areas of finance, especially in asset pricing and dynamic hedging strategies. For example, volatility and the dynamic correlation among markets play a central role as the selection of investment assets and markets and the importance of dynamic hedging are increasing. The hypothesis of a constant correlation of volatility among markets is likely to be incorrect because the correlation will likely to be more volatile as market volatility fluctuates. Thus, there would be bias if we simply use constant correlation to measure the correlation between markets. Especially when the market volatility is unstable, it would also affect the dynamic hedging effect and the calculation of VaR (Value at Risk).
Our results show that there are volatility spillovers among markets. The dynamic correlations among markets are positively related during the Asian crisis. We find that the assumption of a constant correlation would introduce biases in the calculation of correlation among markets and in the estimation of VaR. | en_US |