我国股指期货市场与股票市场风险传导机理研究——基于双变量CAViaR方法

doi:10.12005/orms.2017.0069

运筹与管理 ›› 2017, Vol. 26 ›› Issue (3): 148-156.DOI: 10.12005/orms.2017.0069

我国股指期货市场与股票市场风险传导机理研究——基于双变量CAViaR方法

董珊珊, 冯芸

上海交通大学安泰经济与管理学院,上海 200030

收稿日期:2015-05-10 出版日期:2017-03-25
作者简介:董珊珊(1986-),女,陕西汉中人,博士研究生,研究方向:金融工程;冯芸(1973-),女,海南定安人,教授,博士生导师,研究方向:金融工程,实证金融,公司金融,经济金融全球化与经济发展。
基金资助:
国家自然科学基金项目(71271136)

Risk Transmission Effect between Chinese Stock Index Futures Market and Stock Market ——Based on the Method of B-CAViaR

DONG Shan-shan, FENG Yun

Antai Colledge of Economics & Management, Shanghai Jiaotong University,Shanghai 200030,China

Received:2015-05-10 Online:2017-03-25

摘要/Abstract

摘要： 本文基于日内和日度数据使用双变量CAViaR模型估计了沪深300股指期货和标的指数的风险价值,并基于沪深300股指期货市场日内交易行为角度分析了股指期货和现货市场间日内与日间风险传导作用的差异。结果发现,期货市场日内风险的自相关特征显著高于现货市场,而两个市场的日间自相关性相差甚小,期货市场向现货市场的单向风险溢出效应仅体现在日内信息的传递过程中。与现货市场相比,期货交易的杠杆性以及当日回转交易便利了日内投机、套利交易,因而期货市场日内信息传递效率更高。

关键词: 风险传导, CSI300股指期货, 双变量CAViaR

Abstract: We employ CAViaR model to estimate the value at risk of CSI300 stock index futures and spot index value, and study risk conduction mechanism between Chinese stock index futures market and stock market in view of daily trading behavior, based on the intraday and inter-day data. The results show that the risk of futures market’s intraday autocorrelation characteristic is significantly higher than that of the spot market, but there is no significant different between inter-day autocorrelation, and the risk of futures spillover to the spot market only take place in the intraday process of information transmission. Compare to the cash market, the leveraged and rotary futures trading facilitate intraday speculation and arbitrage, so the efficiency of information transmission is higher in the futures market than that in the cash market.

Key words: Risk Transmission, CSI300 Index futures, B-CAViaR

中图分类号:

F831

董珊珊, 冯芸. 我国股指期货市场与股票市场风险传导机理研究——基于双变量CAViaR方法[J]. 运筹与管理, 2017, 26(3): 148-156.

DONG Shan-shan, FENG Yun. Risk Transmission Effect between Chinese Stock Index Futures Market and Stock Market ——Based on the Method of B-CAViaR[J]. Operations Research and Management Science, 2017, 26(3): 148-156.

参考文献

[1] 张孝岩,沈中华.股指期货推出对中国股票市场波动性的影响研究——基于沪深300股指期货高频数据的实证分析[J].投资研究,2012,(10):112-122.
[2] 陈蓉,郑振龙.无偏估计,价格发现与期货市场效率——期货与现货价格关系[J].系统工程理论与实践,2008.2-11.
[3] 何诚颖,张龙斌,陈薇.基于高频数据的沪深300指数期货价格发现能力研究[J].数量经济技术经济研究,2011,28(5):139-151.
[4] Kavussanos M G, Visvikis I D, Alexakis P D. The lead-lag relationship between cash and stock index futures in a new market[J]. European Financial Management, 2008, 14(5): 1007-1025.
[5] Miller M J, Galloway T M. Index futures trading and stock return volatility: evidence from the introduction of MidCap 400 index futures[J]. The Financial Review, 1997, 32: 845-866.
[6] So R W, Tse Y. Price discovery in the hangsang index markets: index, futures, and the tracker fund[J]. Journal of Futures Markets, 2004, 24: 887-907.
[7] 熊熊,王芳.我国沪深300股指期货仿真交易的价格发现分析[J].天津大学学报:社会科学版,2008,10(4):321-325.
[8] 张宗成,刘少华.沪深300股指期货市场与现货市场联动性及引导关系实证分析[J].中国证券期货,2010,5:4-6.
[9] 熊熊,鲁洋,刘文财.IF1005股指期货合约与沪深300指数的价格发现研究[J].长沙理工大学学报:社会科学版,2010,25(6):38-43.
[10] Yang J, Yang Z, Zhou Y. Intraday price discovery and volatility transmission in stock index and stock index futures markets: Evidence from China[J]. Journal of Futures Markets, 2012, 32(2): 99-121.
[11] 代宏霞,林祥友.股指期货合约存续期价格引导关系的时变性研究[J].投资研究,2012,31(5):127-140.
[12] Hou Y, Li S. Hedging performance of Chinese stock index futures: an empirical analysis using wavelet analysis and flexible bivariate GARCH approaches[J]. Pacific-Basin Finance Journal, 2013, 24: 109-131.
[13] Yi Q, Liang Z. The information efficiency of stock index futures in China[C]. Proceedings of the Seventh International Conference on Management Science and Engineering Management. Springer Berlin Heidelberg, 2014. 1041-1050.[14] 邢精平,周伍阳,季峰.我国股指期货与现货市场信息传递与波动溢出关系研究[J].证券市场导报,2011,2:13-19.
[15] 刘晓彬,李瑜,罗洎.股指期货与现货市场间波动溢出效应探究[J].宏观经济研究,2012,(7):80-86.
[16] 戴佳青,潘和平.沪深 300 股指与期货的高频动态关系检测[J].管理学家:学术版,2011,(7):57-69.
[17] 刘庆富,华仁海.中国股指期货与股票现货市场之间的风险传递效应研究[J].统计研究,2011,(11):84-90.
[18] 乔高秀,刘强.沪深300股指期货与现货市场价格波动与波动溢出效应——基于十五个月高频数据的实证研究[J].投资研究,2012,31(8):132-144.
[19] Zhou W, Dang Y, Gu R. Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm[J]. Physica A: Statistical Mechanics and its Applications, 2013, 392(6): 1429-1438.
[20] 罗洎,王莹.股指期货对证券市场波动性和流动性的影响——基于中国市场的经验研究[J].宏观经济研究,2011,(6):55-61.
[21] 陈俊华,季诺维.股指期货, 噪声交易与风险资产定价[J].投资研究,2014,3:133-144.
[22] 刘心,李淑敏,丁海峰.沪深300指数期货投机风险经验研究[J].财经问题研究,2014,372(11):74-78.
[23] Engle R F, Manganelli S. CAViaR: conditional autoregressive value at risk by regression quantiles[J]. Journal of Business & Economic Statistics, 2004, 22(4): 367-381.
[24] White H, Kim T H, Manganelli S. VAR for VaR: measuring tail dependence using multivariate regression quantiles[J]. Journal of Econometrics, 2015, 187(1): 169-188.
[25] Xiao Z, Koenker R. Conditional quantile estimation for generalized autoregressive conditional heteroscedasticity models[J]. Journal of the American Statistical Association, 2009, 104(488): 1696-1712.
[26] 程展兴.跳跃,流动性变化与价格发现能力研究——基于沪深 300股指期货的分析[J].财贸研究,2013,(3):117-123.
[27] 邢天才,张阁.中国股指期货对现货市场联动效应的实证研究——基于沪深300仿真指数期货数据的分析[J].财经问题研究,2010,(4):48-54.

我国股指期货市场与股票市场风险传导机理研究——基于双变量CAViaR方法

Risk Transmission Effect between Chinese Stock Index Futures Market and Stock Market ——Based on the Method of B-CAViaR

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 1

编辑推荐

Metrics