The dynamic relationships between stock index futures and stock index markets: Evidence from China

This paper employs the VAR-MGARCH models to investigate the price causal relationships and volatility spillovers effects between the CSI 300 index futures and spot markets in China. The 5 min high-frequency data from January 4, 2013 to October 31, 2013 are used. Four different multivariate GARCH models (BEKK, diagonal, constant conditional correlation, and dynamic conditional correlation) are compared and contrasted. It is found that the VAR-DCC-MGARCH model fits the data best and generates results showing that there exist bidirectional price causal relationships between the CSI 300 index futures and spot markets and the CSI 300 futures market tends to play a more dominant role in the price discovery process; there exist bidirectional volatility spillovers effects between the two markets and the index futures and spot markets play the almost equal roles in the volatility information transmission; the CSI 300 index futures and spot markets show a very strong linkage and the dynamic conditional correlations vary from 0.479 to 0.959 with time change. These conclusions indicate that at the maturity stage, the price discovery function of the CSI 300 index futures market has worked well, and the operating efficiency of the CSI 300 index futures market has further improved.