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论文

基于CAViaR模型的沪深300股指期货隔夜风险研究

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  • 1. 华中科技大学经济学院, 湖北 武汉 430074;
    2. 复旦大学经济学院, 上海 200433;
    3. 上海财经大学公共经济与管理学院, 上海 200433

收稿日期: 2015-06-24

  修回日期: 2016-04-01

  网络出版日期: 2016-09-30

基金资助

中央高校基本科研业务费资助项目(2016AB008)

Study on CSI 300 Stock Index Futures Overnight Risk Based on CAViaR Model

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  • 1. School of Economics HUST, Wuhan 430074, China;
    2. School of Economics, Fudan University, Shanghai 200433, China;
    3. School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai 200433, China

Received date: 2015-06-24

  Revised date: 2016-04-01

  Online published: 2016-09-30

摘要

期货隔夜风险的防范历来是投资者关注的热点,本文以沪深300股指期货为研究对象,采用CAViaR模型对普通隔夜风险进行度量,同时还采用新建的CAViaR-EVT模型对极端隔夜风险进行预测,全面地分析了多头VaR和空头VaR在不同分位数的动态变化特征,最后采用Kupiec似然比检验和动态分位数检验对模型进行后测检验。实证结果表明,隔夜收益序列具有右偏、无长期记忆性和尖峰厚尾等典型特征;CAViaR模型对股指期货的普通隔夜风险具有优异的预测能力,其中AS模型的预测效果最好;加入极值理论后,CAViaR-EVT模型同样能很好地刻画极端分位数下隔夜风险的动态演化过程,且其预测结果比EVT和GARCH-EVT模型要更合理。

本文引用格式

简志宏, 曾裕峰, 刘曦腾 . 基于CAViaR模型的沪深300股指期货隔夜风险研究[J]. 中国管理科学, 2016 , 24(9) : 1 -10 . DOI: 10.16381/j.cnki.issn1003-207x.2016.09.001

Abstract

Financial futures market is an important part of modern financial market systems in China. However, financial derivatives have natural properties of high-yield and high risk.Once a futures risk event occurs, it will cause great destructive effect to the whole financial markets.So investors have always been paying great attention to the prevention of futures' overnight risk. However, little work has been done to detect volatility characteristics and risk features of overnight return.
By taking CSI300 stock index futures for sample in this paper,CAViaR model is adopted to directly calculate the common VaR of overnight return. Nevertheless, considering rare data available during optimization in extreme quantiles, the estimation results may be biased. Therefore, a new framework, which combining extreme value theory and CAViaR model, is built to estimate the extreme overnight risk and analyze the dynamic characteristic of different quantiles both in left tail and right tail.Then both Kupiec LR(likelihood ratio) test and dynamic quantile test are used to backtest the accuracy of these models.
The empirical results are summarized as follows: (1) overnight return exhibits stylized facts of positive skewness, leptokurtosis and non-normal distribution. But it lacks of long-term memory property. (2) The three CAViaR models have strong predictivity power to the common overnight risk, among which the AS model performs best, while there is no significant difference between SAV model and IGARCH model. (3) After adding the extreme theory to the CAViaR model, the newly-constructed CAViaR-EVT model still can accurately depict the dynamic process of overnight risk in extreme low quantiles. Moreover, its forecast results are more reasonable than EVT model and GARCH-EVT models.
Important practical and social implications are suggested. The CAViaR model and CAViaR-EVT model offer useful practical approaches to forecast futures' overnight risk. Moreover, it also provides a theoretical reference to carry out effective risk management and monitor activities for the Chinese stock index futures investors and regulators, such as position limits and margin ratio.

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