Intraday dynamic relationships between CSI 300 index futures and spot markets: a high-frequency analysis

Abstract

Based on intraday 5-min high-frequency dataset, this paper empirically analyzes the intraday dynamic relationships between China's CSI 300 index futures and spot markets with vector autoregression (VAR) and multivariate GARCH (MGARCH) models. By comparing four VAR-MGARCH models (dynamic conditional correlation, constant conditional correlation, diagonal and BEKK), the VAR-DCC-MGARCH model is found to fit the data the best and be preferred over the other models. The results of this model show that although there are bidirectional price causal relationships between the CSI 300 index futures and spot markets, the index futures return shock affects the spot market more severely than the spot return shock affects the futures market, indicating that the index futures market dominates the price discovery process between the two markets. There are bidirectional volatility spillovers effects between the CSI 300 index futures and spot markets, and the spillovers effects from index futures to spot almost equal to that from index spot to futures. The time-varying conditional correlations between the CSI 300 index futures and spot markets change from 0.4787 to 0.9594 across time, showing there is a strong positive correlation and linkage effect between the two markets. These results indicate that after a period of time of development, the price discovery performance of the CSI 300 index futures market has begun to function well, and the impact of the CSI 300 index futures market on its underlying spot market has strengthened.

Volatility Spillover between Bist 30 Futures and Spot Markets: A DCC-GARCH Analyses

“…Thus, it was observed that the coefficients for all lagged values were statistically significant in both models. This indicated that both market returns were affected both by their own and other market lagged values (Zhou & Wu, 2016: 1012. Consequently, it could be suggested that there was a causality between the futures and spot market returns in BIST 30 index.…”

“…However, it was also revealed that the intraday volatility in spot market returns had a stronger leading effect in predicting the movements in futures market intraday volatility. Zhou and Wu (2016) analyzed the volatility spillover between CSI 300 index futures and spot markets using the intra-daily five-minute frequency data for January 4 -September 31, 2013 period with four multivariate MGARCH models (DCC, CCC, Diagonal and BEKK MGARCH). The analysis findings demonstrated that different models exhibited different outcomes.…”

Stock index futures trading impact on spot price volatility. The CSI 300 studied with a TGARCH model

“…More recently, Yang et al (2012) investigated price discovery and volatility transmission between index futures and spot markets employing co-integration analysis and an asymmetric Error Correction Model (ECM) with GARCH error on intraday high-frequency data for the period April 16, 2010 to July 30, 2010. Studies by Guo et al (2013), Xie and Mo (2014), Nishimura and Sun (2015), and Zhou and Wu (2016) also indicate an increased volatility following the introduction of CSI 300 index futures. It will be pointed out that this is contrary to our findings.…”

Determination of Causality in Prices of Crude Oil

“…Chevallier (2010) has concluded that the futures prices lead the price discovery process in the EU markets; his research was on CO 2 . Zhou and Wu (2016) performed vector auto-regression (VAR)-MGARCH analysis on high frequency data of China financial futures exchange, and found that the impact of the CSI 300 index futures prices on its underlying spot market has been strengthened over the time. There are few studies which propounds causality from spot to future prices such as Moosa (2002).…”