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M of a kind: A Multivariate Approach at Pairs Trading

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Abstract

Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. Such approach, on its classical formulation, uses information of only two stocks (a stock and its pairs) in the formation of the trading signals. The objective of this paper is to suggest a multivariate version of pairs trading, which will try to create an artificial pair for a particular stock based on the information of m assets, instead of just one. The performance of three different versions of the multivariate approach was assessed for the Brazilian financial market using daily data from 2000 to 2006 for 57 assets. Considering realistic transaction costs, the analysis of performance was conducted with the calculation of raw and excessive returns, beta and alpha calculation, and the use of bootstrap methods for comparing performance indicators against portfolios build with random trading signals. The main conclusion of the paper is that the proposed version was able to beat the benchmark returns and random portfolios for the majority of the parameters. The performance is also found superior to the classic version of the strategy, Perlin (2006b). Another information derived from the research is that the proposed strategy picks up volatility from the data, that is, the annualized standard deviations of the returns are quite high. But, such event is “paid” by high positive returns at the long and short positions. This result is also supported by the positive annualized sharpe ratios presented by the strategy. Regarding systematic risk, the results showed that the proposed strategy does have a statistically significant beta, but it isn’t high in value, meaning that the relationship between return and risk for the trading rules is still attractive.

Suggested Citation

  • Perlin, M., 2007. "M of a kind: A Multivariate Approach at Pairs Trading," MPRA Paper 8309, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:8309
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    References listed on IDEAS

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    1. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero & Maria Dolores Garcia-Artiles, 1997. "Using nearest neighbour predictors to forecast the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 21(1), pages 75-91, January.
    2. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability of Technical Analysis: A Review," AgMAS Project Research Reports 37487, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    3. Dueker, Michael & Neely, Christopher J., 2007. "Can Markov switching models predict excess foreign exchange returns?," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 279-296, February.
    4. Evan Gatev & William N. Goetzmann & K. Geert Rouwenhorst, 2006. "Pairs Trading: Performance of a Relative-Value Arbitrage Rule," The Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 797-827.
    5. repec:bla:eufman:v:4:y:1998:i:1:p:91-103 is not listed on IDEAS
    6. Perlin, M., 2007. "Evaluation of pairs trading strategy at the Brazilian financial market," MPRA Paper 8308, University Library of Munich, Germany.
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    Cited by:

    1. Weiguang Han & Boyi Zhang & Qianqian Xie & Min Peng & Yanzhao Lai & Jimin Huang, 2023. "Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning," Papers 2301.10724, arXiv.org, revised Feb 2023.
    2. Hongshen Yang & Avinash Malik, 2024. "Optimal market-neutral currency trading on the cryptocurrency platform," Papers 2405.15461, arXiv.org, revised Aug 2024.
    3. Haican Diao & Guoshan Liu & Zhuangming Zhu, 2020. "Research on a stock-matching trading strategy based on bi-objective optimization," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-14, December.
    4. Stübinger, Johannes & Mangold, Benedikt & Krauss, Christopher, 2016. "Statistical arbitrage with vine copulas," FAU Discussion Papers in Economics 11/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    5. Bolgun, Evren & Kurun, Engin & Guven, Serhat, 2009. "Dynamic Pairs Trading Strategy For The Companies Listed In The Istanbul Stock Exchange," MPRA Paper 19887, University Library of Munich, Germany.
    6. Chenyanzi Yu & Tianyang Xie, 2021. "Multivariate Pair Trading by Volatility & Model Adaption Trade-off," Papers 2106.09132, arXiv.org.
    7. Krauss, Christopher, 2015. "Statistical arbitrage pairs trading strategies: Review and outlook," FAU Discussion Papers in Economics 09/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    8. Fernando Caneo & Werner Kristjanpoller, 2021. "Improving statistical arbitrage investment strategy: Evidence from Latin American stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4424-4440, July.

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    More about this item

    Keywords

    pairs trading; asset allocation; quantitative strategy;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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