Forecasting volatility in the Singapore stock market

Abstract

Volatility forecasting is a major area in the pricing of derivative securities, such as stock and index options. In this paper, we compare three methods of forecasting volatility. These are the naive method based on historical sample variance, the exponentially weighted moving average (EWMA) method, and the generalised autoregressive conditional heteroscedasticity (GARCH) model. Out-of-sample forecasts of monthly return variances generated by these three methods are compared. The results strongly favour the EWMA method.