IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/8309.html
   My bibliography  Save this paper

M of a kind: A Multivariate Approach at Pairs Trading

Author

Listed:
  • Perlin, M.

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
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/8309/1/MPRA_paper_8309.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Perlin, M., 2007. "Evaluation of pairs trading strategy at the Brazilian financial market," MPRA Paper 8308, University Library of Munich, Germany.
    2. Alessia Naccarato & Andrea Pierini & Giovanna Ferraro, 2021. "Markowitz portfolio optimization through pairs trading cointegrated strategy in long-term investment," Annals of Operations Research, Springer, vol. 299(1), pages 81-99, April.
    3. Bruno Breyer Caldas & João Frois Caldeira & Guilherme Vale Moura, 2016. "Is Pairs Trading Performance Sensitive To The Methodologies?: A Comparison," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 130, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Sayat R. Baronyan & İ. İlkay Boduroğlu & Emrah Şener, 2010. "Investigation Of Stochastic Pairs Trading Strategies Under Different Volatility Regimes," Manchester School, University of Manchester, vol. 78(s1), pages 114-134, September.
    5. Hossein Rad & Rand Kwong Yew Low & Robert Faff, 2016. "The profitability of pairs trading strategies: distance, cointegration and copula methods," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1541-1558, October.
    6. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2017. "Searching for Inefficiencies in Exchange Rate Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 405-432, March.
    7. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    8. 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.
    9. Andreas Mikkelsen, 2018. "Pairs trading: the case of Norwegian seafood companies," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 303-318, January.
    10. Stephan Schulmeister, 2005. "Components of the Profitability of Technical Currency Trading," WIFO Working Papers 263, WIFO.
    11. 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.
    12. Fabio Pizzutilo, 2013. "A Note on the Effectiveness of Pairs Trading For Individual Investors," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 763-771.
    13. Charlotte, Christiansen, 2011. "Intertemporal risk-return trade-off in foreign exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(4), pages 535-549, October.
    14. R. Todd Smith & Xun Xu, 2017. "A good pair: alternative pairs-trading strategies," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(1), pages 1-26, February.
    15. Schulmeister, Stephan, 2006. "The interaction between technical currency trading and exchange rate fluctuations," Finance Research Letters, Elsevier, vol. 3(3), pages 212-233, September.
    16. Estefanía Montoya-Cruz & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "Exploring Arbitrage Strategies in Corporate Social Responsibility Companies," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    17. 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.
    18. João Frois Caldeira & Gulherme Valle Moura, 2013. "Selection of a Portfolio of Pairs Based on Cointegration: A Statistical Arbitrage Strategy," Brazilian Review of Finance, Brazilian Society of Finance, vol. 11(1), pages 49-80.
    19. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
    20. Laila Taskeen Qazi & Atta Ur Rahman & Saleem Gul, 2015. "Which Pairs of Stocks should we Trade? Selection of Pairs for Statistical Arbitrage and Pairs Trading in Karachi Stock Exchange," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 54(3), pages 215-244.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:8309. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.