Research On Statistical Arbitrage Strategy Of Chinese Financial Market Based On Copula Theory

Nowadays,there are many links in the financial market.It has been a hot topic in the financial field to explore and use the correlation of financial series.The theory of statistical arbitrage develops on the basis of correlation structure,which provides important theoretical basis and operational tools for investors in various financial fields to pursue stable returns.With the advent of the era of big data,financial data is becoming more and more massive,and traditional correlation analysis tools also expose many disadvantages.Copula theory,especially Vine Copula method,solves the problem that the traditional correlation tools are too dependent on the edge distribution form,and makes the described correlation structure more practical.First of all,this paper summarizes the domestic and foreign literature on Copula theory and statistical arbitrage,and grasps the general development context and cutting-edge direction of the theory.Then,this paper introduces Copula theory in detail,starting from the edge distribution modeling of financial series,and then introduces Copula theoretical knowledge and the method of selecting the appropriate Vine structure,then analyzes how to select the appropriate Pair Copula function type,and finally gives the parameter estimation and test method of the model.Finally,using the correlation structure of financial series based on Copula theory,this paper can get the calculation methods of Kendall rank correlation coefficient,Spearman rank correlation coefficient and tail correlation coefficient.Next,this paper systematically reviews the definition of statistical arbitrage,matching transaction process and common models,focusing on cointegration arbitrage model,stochastic spread model and minimum distance model,and designs empirical analysis based on the basic concept of statistical arbitrage.Based on the above theoretical knowledge,this paper establishes the correlation structure among the varieties of Chinas futures market based on Vine Copula method,selects the varieties with strong correlation to construct the trading pairs,and then designs the statistical arbitrage strategy based on the tail correlation coefficient.Finally,this paper uses the JoinQuant platform to test the historical data with the above strategies,and the test results show that the above strategies can obtain stable benefits.This paper applies the latest results of Copula theory to Chinas financial market,and explores a set of correlation structure analysis methods applicable to Chinas financial market,which will provide full support and help to the theories related to portfolio management,risk hedging,risk management,etc.in this field.At the same time,the research results of this paper have certain practical significance for the financial industry.For market participants,the research content of this paper can provide feasible solutions for institutional and individual investors in the construction of investment portfolio,and provide full reference for the implementation of statistical arbitrage strategy and the construction of investment portfolio based on this strategy.Market participants can further develop financial products,hedge risks,manage risks and other business in accordance with the correlation structure of financial transaction varieties studied in this paper.For market regulators,relying on the correlation structure and arbitrage strategy of this paper,this paper can provide strong data support and sample analysis for them to further develop variety trading rules and improve trading system deeply in the future.