China Accounting and Finance Review

, 18:2

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Realised Volatility Forecasts for Stock Index Futures Using the HAR Models with Bayesian Approaches *

  • Jiawen LuoAffiliated withLingnan College, Sun Yat-sen University Email author 
  • , Langnan ChenAffiliated withLingnan College, Sun Yat-sen University


We investigate the realised volatility (RV) forecasts for the short, mid, and long term by developing the HAR models with Bayesian approaches and employing the high-frequency data of the China Stock Index 300 (CSI300) future for the period from 16 April 2010 to 21 May 2014. We also evaluate the performances of competing models for both in-sample forecasts and out-of-sample forecasts. We find that the proposed HAR-type models with Bayesian approaches capture the time-varying properties of parameters and predictor sets. We also find that the HAR-type models with Bayesian approaches have superior forecast performance for both in-sample forecasts and out-of-sample forecasts as compared with the benchmark HAR-type models.


Realised Volatility Forecast Stock Index Futures HAR Model Bayesian Approaches Time-varying