Dynamic Interactions between Intraday Returns and Trading Volume on the CSI 300 Index Futures: An Application of an SVAR Model

Susheng Wang, Guanglu Li and Junbo Wang

Mathematical Problems in Engineering, 2019, vol. 2019, 1-18

Abstract:

The results of data description using ten samples of high-frequency data to describe the intraday characteristics of the CSI 300 index futures show that there is no significant summit and fat tail phenomenon. The Granger causality test shows that there is not only a two-way Granger causality between returns and trading volume but also an instantaneous causality relationship. Therefore, the A-type SVAR models are identified and estimated after setting up constraints, and all the models are tested stable. Subsequent variance decomposition results show that the residual disturbance of returns can be explained more than 99.9% by its lagged terms; the residual disturbance of trading volume explained by its lagged terms and returns is quite different, and the range of interpretation is very wide. The impulse response results show that the market responds very quickly to new information. When a shock is reached, the market can reach a new equilibrium point after about three observation time periods. This shows that the market is able to digest new information quickly, and arbitrage trading becomes very difficult in this market.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8676531

DOI: 10.1155/2019/8676531

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