IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v28y2023i1p193-207.html
   My bibliography  Save this article

The profitability of pair trading strategy in stock markets: Evidence from Toronto stock exchange

Author

Listed:
  • GholamReza Keshavarz Haddad
  • Hassan Talebi

Abstract

Market practitioners and speculators attempt to make benefits from the existence of market price gaps and profit opportunities by arbitrage strategies. Although some investors trade stocks based on the available financial and fundamental information of a particular share, there are others who make profits by risk hedging and swing trading opportunities. One of these strategies is pairs trading, which is a sub‐category of statistical arbitrage. Pairs trading can assure reasonably a risk‐free profit gaining. This paper aims to make a hypothetical portfolio composed of pairs of stocks by exploring a significant association between their prices in the Toronto Stock Exchange, TSX. We compare the profitability of distance, co‐integration, and copula functions as the pair's selection and trading strategy devices in TSX over January 2017 to June 2020. Our results show that the highest profitability comes from trading by the copula method. Our time frame includes two heterogeneous pre and post COVID‐19 periods. Although the financial markets are struggling with a hard situation over the COVID‐19 days, the performance of the methodologies is not affected by the crisis.

Suggested Citation

  • GholamReza Keshavarz Haddad & Hassan Talebi, 2023. "The profitability of pair trading strategy in stock markets: Evidence from Toronto stock exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 193-207, January.
  • Handle: RePEc:wly:ijfiec:v:28:y:2023:i:1:p:193-207
    DOI: 10.1002/ijfe.2415
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.2415
    Download Restriction: no

    File URL: https://libkey.io/10.1002/ijfe.2415?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Nicolas Huck & Komivi Afawubo, 2015. "Pairs trading and selection methods: is cointegration superior?," Applied Economics, Taylor & Francis Journals, vol. 47(6), pages 599-613, February.
    2. Binh Do & Robert Faff, 2012. "Are Pairs Trading Profits Robust To Trading Costs?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 35(2), pages 261-287, June.
    3. 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.
    4. 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.
    5. Christopher Krauss, 2017. "Statistical Arbitrage Pairs Trading Strategies: Review And Outlook," Journal of Economic Surveys, Wiley Blackwell, vol. 31(2), pages 513-545, April.
    6. Nicolas Huck & Komivi Afawubo, 2015. "Pairs trading and selection methods: is cointegration superior?," Post-Print hal-01369852, HAL.
    7. Nicolas Huck, 2013. "The high sensitivity of pairs trading returns," Applied Economics Letters, Taylor & Francis Journals, vol. 20(14), pages 1301-1304, September.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    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. Marianna Brunetti & Roberta de Luca, 2022. "Sensitivity of profitability in cointegration-based pairs trading," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0090, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    2. Marianna Brunetti & Roberta De Luca, 2023. "Pre-selection in cointegration-based pairs trading," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1611-1640, December.
    3. Flori, Andrea & Regoli, Daniele, 2021. "Revealing Pairs-trading opportunities with long short-term memory networks," European Journal of Operational Research, Elsevier, vol. 295(2), pages 772-791.
    4. 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.
    5. Danni Chen & Jing Cui & Yan Gao & Leilei Wu, 2017. "Pairs trading in Chinese commodity futures markets: an adaptive cointegration approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(5), pages 1237-1264, December.
    6. 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.
    7. Clegg, Matthew & Krauss, Christopher, 2016. "Pairs trading with partial cointegration," FAU Discussion Papers in Economics 05/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    8. Marianna Brunetti & Roberta De Luca, 2023. "Pairs trading in the index options market," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 145-173, March.
    9. Sánchez-Granero, M.A. & Balladares, K.A. & Ramos-Requena, J.P. & Trinidad-Segovia, J.E., 2020. "Testing the efficient market hypothesis in Latin American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    10. Stübinger, Johannes, 2018. "Statistical arbitrage with optimal causal paths on high-frequencydata of the S&P 500," FAU Discussion Papers in Economics 01/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    11. 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.
    12. Sabino da Silva, Fernando A.B. & Ziegelmann, Flavio A. & Caldeira, João F., 2023. "A pairs trading strategy based on mixed copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 16-34.
    13. Han, Chulwoo & He, Zhaodong & Toh, Alenson Jun Wei, 2023. "Pairs trading via unsupervised learning," European Journal of Operational Research, Elsevier, vol. 307(2), pages 929-947.
    14. Zhe Huang & Franck Martin, 2017. "Optimal pairs trading strategies in a cointegration framework," Working Papers halshs-01566803, HAL.
    15. Stübinger, Johannes & Endres, Sylvia, 2017. "Pairs trading with a mean-reverting jump-diffusion model on high-frequency data," FAU Discussion Papers in Economics 10/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    16. Boming Ning & Prakash Chakraborty & Kiseop Lee, 2023. "Optimal Entry and Exit with Signature in Statistical Arbitrage," Papers 2309.16008, arXiv.org, revised Mar 2024.
    17. Baiquan Ma & Robert Ślepaczuk, 2022. "The profitability of pairs trading strategies on Hong-Kong stock market: distance, cointegration, and correlation methods," Working Papers 2022-02, Faculty of Economic Sciences, University of Warsaw.
    18. Andreas Mikkelsen, 2018. "Pairs trading: the case of Norwegian seafood companies," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 303-318, January.
    19. Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy," Papers 1811.09312, arXiv.org, revised Jul 2022.
    20. Law, K.F. & Li, W.K. & Yu, Philip L.H., 2018. "A single-stage approach for cointegration-based pairs trading," Finance Research Letters, Elsevier, vol. 26(C), pages 177-184.

    More about this item

    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:wly:ijfiec:v:28:y:2023:i:1:p:193-207. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.