Does VPIN provide predictive information for realized volatility forecasting: evidence from Chinese stock index futures market

Conghua Wen, Fei Jia and Jianli Hao

China Finance Review International, 2020, vol. 13, issue 2, 285-303

Abstract: Purpose - Using intraday data, the authors explore the forecast ability of one high frequency order flow imbalance measure (OI) based on the volume-synchronized probability of informed trading metric (VPIN) for predicting the realized volatility of the index futures on the China Securities Index 300 (CSI 300). Design/methodology/approach - The authors employ the heterogeneous autoregressive model for realized volatility (HAR-RV) and compare the forecast ability of models with and without the predictive variable, OI. Findings - The empirical results demonstrate that the augmented HAR model incorporating OI (HARX-RV) can generate more precise forecasts, which implies that the order imbalance measure contains substantial information for describing the volatility dynamics. Originality/value - The study sheds light on the relation between high frequency trading behavior and volatility forecasting in China's index futures market and reveals the underlying market mechanisms of liquidity-induced volatility.

Keywords: Realized volatility; Volatility forecasting; HAR model; Trading behavior; Equity futures; G13; G15; G17 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eme:cfripp:cfri-05-2020-0049

DOI: 10.1108/CFRI-05-2020-0049

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