Forecasting volatility data based on Wavelet transforms and ARIMA model

This article suggests a novel technique for forecasting the volatility data based on Wavelet transforms and ARIMA model. The volatility data are decomposed via Wavelet transforms. Then, the future observations of this series are forecasted using a suitable and best fitted ARIMA model. Daily prices from Amman Stocks Market (Jordan) from 1993 until 2009 are used in this study.