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


  • GholamReza Keshavarz Haddad
  • Hassan Talebi


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.

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  • 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

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    References listed on IDEAS

    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.
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