Abstract

In stock markets, the price is fluctuating around its average value with the time being. One of the volatilities is the variance heteroscedasticity. It is found that auto-regressive conditional heteroscedasticity (ARCH) model provides an alternative approach for the simulation of stock heteroscedasticity. In this paper, the application of ARCH and its modified models is presented for the risk analysis based on the stock index of America, Europe, China and other countries in Asia Pacific. GARCH-M model is used to test the long-term volatility self-similarity and the correlation between risk and return; TGARCH model is introduced to test the volatility leverage effect; EGARCH model is applied to verify the asymmetry heteroscedasticity of stock price fluctuation.

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