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Stock Return Distribution Assumptions’ Impacts upon Market Volatility Forecasting: Experiences from Australian Securities Exchange

In the context of a continually changing and reforming financial market, stock market volatility plays a vital role in indicating macroeconomic environment changes, market participants’ expectation and interaction mechanism. Market volatility research has been conducted by worldwide academics from different perspectives. However, different backgrounds, assumptions, methodologies and intentions have led to heterogeneous volatility models, making volatility forecasting a controversial topic. This paper tests the hypothesis that stock return distribution assumptions underlying Australian Securities Exchange's Volatility influence the performance of volatility forecasting. The methodologies mainly involve empirical analysis, for instance, three GARCH models in terms of GARCH-Normal (GARCH-N), GARC-Student-t (GARCH-ST) and GARCH-Skewed Generalised Error Distribution (GARCH-SGED) are applied. Not only the daily returns, realised weekly and monthly volatilities of SP volatility dependence and volatility-correlation co-movement may reduce the benefits of stock diversification.