Title :
Intraday Volume-Volatility Dynamics in CSI 300 Futures Market
Author :
Yu Zhen ; Wang Susheng
Author_Institution :
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen, China
Abstract :
Using 1-min transaction data, this study investigates the relationship between volume and volatility in CSI 300 futures market in China. Unit root test indicates that return series are stationary. LB-Q and ARCH-LM statistics confirm volatility clustering and time-vary volatility. ARMA (2, 2)-EGARCH (1, 1) model find evidence of GARCH effect, and positive shocks have a greater impact on volatility than negative shocks. Furthermore, the coefficients of both contemporaneous and lagged volume are positive and significant statistically, indicate that volume as information flow indicators, may explain the volatility, Both MDH and SIA hypothesizes are verified in China. These findings have significant implications for the traders and policymakers.
Keywords :
statistical distributions; stock markets; 1-min transaction data; ARCH-LM statistics; ARMA(2,2)-EGARCH(1,1) model; CSI 300 futures market; China; China Securities Index; GARCH effect; LB-Q statistics; MDH hypothesis; SIA hypothesis; intraday volume-volatility dynamics; mixture of distributions hypothesis; negative shocks; policymakers; positive shocks; return series; root test; sequential information arrival models; time-vary volatility; traders; volatility clustering; Correlation; Economics; Electric shock; Equations; Indexes; Mathematical model; Solid modeling; index futures; mixture of distributions hypothesis; sequential information arrival hypothesis; volume-volatility dynamics;
Conference_Titel :
Business Intelligence and Financial Engineering (BIFE), 2013 Sixth International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4778-2
DOI :
10.1109/BIFE.2013.84