股指期货对现货时变相依结构的多尺度研究

Multi-scale Study on Time-varying Dependency Structure between the Stock Index Futures and the Actual

股指期货与现货之间的相依结构是Copula理论在金融分析中套期保值、组合风险对冲及价格发现等应用的热点。考虑到新息对价格的非对称冲击和相依结构的时变特征,利用GJR-GARCH模型对股指期货和现货的收益率序列建模,选用DCC方程刻画二者之间时变相关系数的演化结构,构建时变T-Copula-GJR-GARCH模型。针对沪深300指数现货与期货5～60分钟的高频数据,分尺度拟合时变T-Copula-GJR-GARCH(1,1)-t模型,结果表明相依结构随时间尺度变化而变化,这或许可由市场微观结构差异及投资者的异质性所解释,进而本文从多尺度的视角揭示了我国股指期货与现货之间的时变相依模式。

Copula theory is very popular to model the dependency structure between the price of future and spot market in financial analysis including risk hedge,hedging portfolio and price discovery.This paper considers the innovation asymmetric impact on the price and the time-varying characteristics of the dependency structure,and constructs a time-varying T-Copula-GJR-GARCH model by using a GJR-GARCH model to fit the two returns,respectively.By choosing the DCC equation to depict the dynamic structure of the time-varying coefficient,and based on high frequency price data from 5 to 60 minute of the Hu-Shen 300 index futures and stock market,we establish a time-varying T-Copula-GJR-GARCH（1,1）-T model by time-scale.The results indicate the dependent structure changes over time-scale,which may be explained by the market microstructure and heterogeneity of the investors.Hence,this paper reveals the potential time-varying dependency patterns between China＇s stock index futures and spot market at multi-scale time horizons.