Forecasting realized volatility in a changing world: A dynamic model averaging approach

Yudong Wang, Feng Ma, Yu Wei and Chongfeng Wu

Journal of Banking & Finance, 2016, vol. 64, issue C, 136-149

Abstract: In this study, we forecast the realized volatility of the S&P 500 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. A dynamic model averaging (DMA) approach is used to combine the forecasts of the individual models. Our empirical results suggest that DMA can generate more accurate forecasts than individual model in both statistical and economic senses. Models that use time-varying parameters have greater forecasting accuracy than models that use the constant coefficients. The superiority of time-varying parameter models is also found in volatility density forecasting.

Keywords: S&P 500 index; Realized volatility; Dynamic model averaging; Time-varying parameters; Portfolio (search for similar items in EconPapers)
JEL-codes: C22 C58 G13 G14 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (171)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:64:y:2016:i:c:p:136-149

DOI: 10.1016/j.jbankfin.2015.12.010

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