Does VPIN provide predictive information for realized volatility forecasting: evidence from Chinese stock index futures market
China Finance Review International
ISSN: 2044-1398
Article publication date: 18 November 2020
Issue publication date: 7 April 2023
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
Acknowledgements
This research was funded by Research Development Fund (RDF) of Xi'an Jiaotong-Liverpool University, Grant number: RDF18-02-08.
Citation
Wen, C., Jia, F. and Hao, J. (2023), "Does VPIN provide predictive information for realized volatility forecasting: evidence from Chinese stock index futures market", China Finance Review International, Vol. 13 No. 2, pp. 285-303. https://doi.org/10.1108/CFRI-05-2020-0049
Publisher
:Emerald Publishing Limited
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