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Forecasting the realized range-based volatility using dynamic model averaging approach

Jing Liu, Yu Wei, Feng Ma and M.I.M. Wahab

Economic Modelling, 2017, vol. 61, issue C, 12-26

Abstract: In this study, we forecast the realized range-based volatility (RRV) using the heterogeneous autoregressive realized range-based volatility (HAR-RRV) model and its various extensions, which are called HAR-RRV-type models. We first consider the time-varying property of those models’ parameters using the dynamic model averaging (DMA) approach and evaluate the forecasting performance of three types: individual HAR-RRV-type models, combined models with constant weights, and combined models with time-varying weights. Our out-of-sample empirical results show that combined models with time-varying weights can not only generate more accurate forecasts, but also beat individual models and combined models with constant weights.

Keywords: Volatility forecasting; Realized range-based volatility; Dynamic model averaging; Combined models (search for similar items in EconPapers)
JEL-codes: C22 C52 C55 (search for similar items in EconPapers)
Date: 2017
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