Application of EGARCH Model to Estimate Financial Volatility of Daily Returns: The empirical case of China

Abstract

The financial crisis generates a practical case to measure the variation of return volatility in high fluctuating stock markets that may exhibit different characteristics from the relatively stable stock market. Hence, the main purpose of this paper is to analyze whether the long term volatility is more extensive during the crisis period than before the crisis, and compare the movements of the return volatility of Chinese stock market to the other stock markets before and throughout the crisis period. We apply the daily data from January 2000 to April 2010 and split the time series into two parts: before the crisis and during the crisis period. The analysis is based on employing both GARCH and EGARCH models. The empirical results suggest that EGARCH model fits the sample data better than GARCH model in modeling the volatility of Chinese stock returns. The result also shows that long term volatility is more volatile during the crisis period. Bad news produces stronger effect than good news for the Chinese stock market during the crisis.