The profitability of pairs trading strategies: distance, cointegration and copula methods

We perform an extensive and robust study of the performance of three different pairs trading strategies—the distance, cointegration and copula methods—on the entire US equity market from 1962 to 2014 with time-varying trading costs. For the cointegration and copula methods, we design a computationally efficient two-step pairs trading strategy. In terms of economic outcomes, the distance, cointegration and copula methods show a mean monthly excess return of 91, 85 and 43 bps (38, 33 and 5 bps) before transaction costs (after transaction costs), respectively. In terms of continued profitability, from 2009, the frequency of trading opportunities via the distance and cointegration methods is reduced considerably, whereas this frequency remains stable for the copula method. Further, the copula method shows better performance for its unconverged trades compared to those of the other methods. While the liquidity factor is negatively correlated to all strategies’ returns, we find no evidence of their correlation to market excess returns. All strategies show positive and significant alphas after accounting for various risk-factors. We also find that in addition to all strategies performing better during periods of significant volatility, the cointegration method is the superior strategy during turbulent market conditions.

[1]  James Angel When Finance Meets Physics: The Impact of the Speed of Light on Financial Markets and Their Regulation , 2014, 1401.2982.

[2]  Carol L. Clark How to Keep Markets Safe in the Era of High-Speed Trading , 2012 .

[3]  Martin Weber,et al.  On the Determinants of Pairs Trading Profitability , 2014 .

[4]  Yoav Freund,et al.  Automated trading with boosting and expert weighting , 2010 .

[5]  M. Perlin Evaluation of pairs-trading strategy at the Brazilian financial market , 2009 .

[6]  Sheridan Titman,et al.  On Persistence in Mutual Fund Performance , 1997 .

[7]  M. Vaihekoski,et al.  Profitability of Pairs Trading Strategy In and Illiquid Market with Multiple Share Classes , 2012 .

[8]  Gregor N. F. Weiss,et al.  Forecasting Portfolio-Value-At-Risk with Nonparametric Lower Tail Dependence Estimates , 2015 .

[9]  E. Fama,et al.  A Five-Factor Asset Pricing Model , 2014 .

[10]  Yuan Wu,et al.  Copula-Based Pairs Trading Strategy , 2013 .

[11]  Martin Eling,et al.  Does the Choice of Performance Measure Influence the Evaluation of Hedge Funds? , 2007 .

[12]  R. Faff,et al.  Enhancing Mean-Variance Portfolio Selection by Modeling Distributional Asymmetries , 2013 .

[13]  Ba Chu,et al.  Recovering copulas from limited information and an application to asset allocation , 2011 .

[14]  Luca Vogt,et al.  When Genius Failed The Rise And Fall Of Long Term Capital Management , 2016 .

[15]  Chi-Guhn Lee,et al.  Pairs trading: optimal thresholds and profitability , 2014 .

[16]  Nicolas Huck,et al.  Pairs trading and selection methods: is cointegration superior? , 2015 .

[17]  E. Fama,et al.  Common risk factors in the returns on stocks and bonds , 1993 .

[18]  Mark S. Seasholes,et al.  Understanding the Profitability of Pairs Trading , 2005 .

[19]  João Caldeira,et al.  Selection of a Portfolio of Pairs Based on Cointegration: A Statistical Arbitrage Strategy , 2013 .

[20]  Nicolas Huck,et al.  Pairs trading: does volatility timing matter? , 2015 .

[21]  C. Granger,et al.  Co-integration and error correction: representation, estimation and testing , 1987 .

[22]  F. Longin,et al.  Is the Correlation in International Equity Returns Constant: 1960-90? , 1995 .

[23]  G. Vidyamurthy Pairs Trading: Quantitative Methods and Analysis , 2004 .

[24]  Nicolas Huck,et al.  Pairs trading and outranking: The multi-step-ahead forecasting case , 2010, Eur. J. Oper. Res..

[25]  Martin Eling,et al.  Sufficient Conditions for Expected Utility to Imply Drawdown-Based Performance Rankings , 2010 .

[26]  William N. Goetzmann,et al.  Pairs Trading: Performance of a Relative Value Arbitrage Rule , 1998 .

[27]  Alexander Galenko,et al.  Trading in the Presence of Cointegration , 2012 .

[28]  Yuan Wu,et al.  Pairs trading: A copula approach , 2013 .

[29]  A. Frigessi,et al.  Pair-copula constructions of multiple dependence , 2009 .

[30]  James Jayko A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation . By Bookstaber Richard. John Wiley and Sons, 2007, ISBN 978-0-471-22727-4, 288 pages. , 2008, Journal of Pension Economics and Finance.

[31]  M. Dempster,et al.  A real-time adaptive trading system using genetic programming , 2001 .

[32]  Andrew J. Patton On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation , 2002 .

[33]  Steve Y. Yang,et al.  Gaussian process-based algorithmic trading strategy identification , 2012 .

[34]  Martin Eling,et al.  Does the Measure Matter in the Mutual Fund Industry? , 2008 .

[35]  Jamie Alcock,et al.  Canonical Vine Copulas in the Context of Modern Portfolio Management: Are They Worth It? , 2013 .

[36]  Satishs Iyengar,et al.  Multivariate Models and Dependence Concepts , 1998 .

[37]  T. Bogomolov Pairs Trading in the Land Down Under , 2010 .

[38]  Gregor N. F. Weiß,et al.  Mixture Pair-Copula-Constructions , 2015 .

[39]  Robert W. Faff,et al.  Diamonds vs. Precious Metals: What Shines Brightest in Your Investment Portfolio? , 2015 .

[40]  Asymmetric increasing trends in dependence in international equity markets. , 2014 .

[41]  R. Jagannathan,et al.  An Anatomy of Pairs Trading: The Role of Idiosyncratic News, Common Information and Liquidity , 2008 .

[42]  R. Faff,et al.  Does Simple Pairs Trading Still Work? , 2010 .

[43]  Yuan Wu,et al.  Pairs Trading with Copulas , 2016, The Journal of Trading.

[44]  Yan-Xia Lin,et al.  Loss protection in pairs trading through minimum profit bounds: A cointegration approach , 2006, Adv. Decis. Sci..

[45]  Timofei Bogomolov,et al.  Pairs trading based on statistical variability of the spread process , 2013 .

[46]  Nicolas Huck,et al.  Pairs selection and outranking: An application to the S&P 100 index , 2009, Eur. J. Oper. Res..

[47]  T. Hendershott,et al.  High Frequency Trading and Price Discovery , 2013, SSRN Electronic Journal.

[48]  R. Faff,et al.  Are Pairs Trading Profits Robust to Trading Costs , 2012 .