Cross-species Statistical Arbitrage Strategy Based On Cointegration-ecm

Under the circumstance of increasing economic downward pressure,the difficulty of relying on traditional investment methods to increase profits is increasing.This requires a stable and reliable investment strategy to replace traditional investment methods.The cross-species arbitrage strategy based on statistical arbitrage is one.A quantitative investment strategy that can replace traditional investment methods.Quantitative investment is an investment strategy between active investment and passive investment.It requires investors to actively design trading strategies and then execute the trading procedures based on the computer programming language.The statistical arbitrage strategy is a kind of investment strategy that is more commonly used in the field of investment.This strategy greatly reduces the market risk by constructing a combination of long and short arbitrage,and the strategy's income trend is therefore largely independent of the market.This makes it possible to obtain stable and reliable returns.In the application of many statistical arbitrage strategies,most of them use the cointegration method to construct the statistical arbitrage model.In this paper,the error correction term is added on the basis of cointegration,and the statistical arbitrage strategy is constructed by the cointegration-error correction model.Based on this,the soybean oil is constructed.The arbitrage combination with the palm oil futures contract forms a cross-species commodity futures arbitrage scheme based on statistical arbitrage,providing investors with stable and reliable investment strategy choices.In this paper,the soybean oil and palm oil with strong correlation are taken as examples to construct the arbitrage combination based on the cointegration-error correction model.Firstly,the data is divided into estimated samples and backtest samples,and the correlation and stability of the data are analyzed.Then the model is used to determine the combination ratio of the arbitrage combination,the trading signals,and the arbitrage transaction to determine the reliability of the model.The estimated sample optimizes the trading parameters and uses the backtest samples to verify the validity of the trading parameters.Finally,the effectiveness of the statistical arbitrage strategy is analyzed by indicators such as annualized rate of return and Sharpe ratio.The backtest results show that the model performance after parameter optimization is better than that of the model with fixed parameters.Under the optimal parameters of the two groups,the annualized yield of the model is 51% and 28%,respectively.49%,10% increase,and all the back-test indicators are better than the Wind Commodity Index,indicating that this strategy has a stable and reliable profit characteristics.