基于协整理论的DFT-GARCH模型的统计套利研究  

Statistical Arbitrage Research of DFT-GARCH Model Based on Cointegration Theory

作　　者：方军 李星野[1] FANG Jun;LI Xingye(College of Management,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学管理学院

出　　处：《经济数学》2019年第2期57-62,共6页Journal of Quantitative Economics

摘　　要：现有的统计套利策略大多建立在协整理论和GARCH模型的基础上.离散Fourier变换(DFT)的思想可以挖掘价差序列周期性、非线性的特征,保证其在拟合和预测中的精确度.利用沪铜期货合约的收盘价数据进行实证分析,研究结果表明:在高频数据下,新模型对数据的拟合和预测效果要明显优于传统的套利模型,在相同的交易规则下,新模型的套利成功率和收益率都高于传统的统计套利模型.Most of the existing statistical arbitrage strategies are based on the cointegration theory and the GARCH model.The idea of discrete Fourier transform (DFT) can exploit the periodic and nonlinear characteristics of the spread se quence to ensure its accuracy in fitting and prediction.Using the closing price data of copper futures con tract in the Shanghai futures exchanges for empirical analysis,the results show that under the high-frequency data,the new model fits and predicts the data better than the traditional arbitrage model.Under the same trading rules,the arbitrage success rate and yield of the new model are higher than the traditional one.

关 键 词：数量经济学 统计套利 协整理论 GARCH模型 离散Fourier变换 

分 类 号：F224.O[经济管理—国民经济]