FORECASTING REALIZED VOLATILITY DYNAMICALLY BASED ON ADJUSTED DYNAMIC MODEL AVERAGING (AMDA) APPROACH: EVIDENCE FROM CHINA’S STOCK MARKET

Abstract

In this study, we forecast the realized volatility of the CSI 300 index using the heterogeneous autoregressive model for realized volatility (HAR-RV) and its various extensions. Our models take into account the time-varying property of the models’ parameters and the volatility of realized volatility. The adjusted dynamic model averaging (ADMA) approach, is used to combine the forecasts of the individual models. Our empirical results suggest that ADMA can generate more accurate forecasts than DMA method and alternative strategies. Models that use time-varying parameters have greater forecasting accuracy than models that use the constant coefficients.