High Frequency and Dynamic Pairs Trading Based on Statistical Arbitrage Using a Two-Stage Correlation and Cointegration Approach

George J. Miao

56 citations0/0 files storedInternational Journal of Economics and Finance

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Financial Markets and Investment Strategies Financial Risk and Volatility Modeling Stock Market Forecasting Methods

Abstract

In this paper, a high frequency and dynamic pairs trading system is proposed, based on a market-neutral statistical arbitrage strategy using a two-stage correlation and cointegration approach. The proposed pairs trading system was applied to equity trading in U.S. equity markets in any type of market cycle condition to capture statistical mispricing between the prices of each stock pair based on its residuals and to model the stock pairs naturally as a mean-reversion process. The proposed pairs trading system was tested for out-of-sample testing periods with high frequency stock data from 2012 and 2013. Our trading strategy yields cumulative returns up to 56.58% for portfolios of stock pairs, well exceeding the S&P 500 index performance by 34.35% over a 12-month trading period. The proposed trading strategy achieved a monthly 2.67 Sharpe ratio and an annual 9.25 Sharpe ratio. Furthermore, the proposed pairs trading system performed well during the two months in which the S&P 500 index had negative returns. Thus, the trading system might be especially more profitable at times when the U.S. stock market performed poorly. Therefore, the performance returns of the proposed pairs trading system were relatively market-neutral and were positive regardless of the performance of the S&P 500 index.

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References

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