IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v93y2026ics154461232600173x.html

Pairs trading — Selection via scoring systems

Author

Listed:
  • Reichmann, Lukas

Abstract

In this Paper I determine the driving factors for successful stock pairs to further improve the pairs selection process while utilizing cointegration methods. I test my selection based on regression coefficients on two different trading approaches which both are based on cointegration, but handle identical pairs selections in consecutive periods differently. This is tested against the standard selection procedure based on the sum of squared distances. According to my findings I can identify the possible driving forces for successful stock pair selection and generate more competitive returns.

Suggested Citation

  • Reichmann, Lukas, 2026. "Pairs trading — Selection via scoring systems," Finance Research Letters, Elsevier, vol. 93(C).
  • Handle: RePEc:eee:finlet:v:93:y:2026:i:c:s154461232600173x
    DOI: 10.1016/j.frl.2026.109642
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461232600173X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2026.109642?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Robert Engle & Clive Granger, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Mark Cummins & Andrea Bucca, 2012. "Quantitative spread trading on crude oil and refined products markets," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1857-1875, December.
    3. Taewook Kim & Ha Young Kim, 2019. "Optimizing the Pairs-Trading Strategy Using Deep Reinforcement Learning with Trading and Stop-Loss Boundaries," Complexity, Hindawi, vol. 2019, pages 1-20, November.
    4. 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.
    5. Huck, Nicolas, 2009. "Pairs selection and outranking: An application to the S&P 100 index," European Journal of Operational Research, Elsevier, vol. 196(2), pages 819-825, July.
    6. Huck, Nicolas, 2010. "Pairs trading and outranking: The multi-step-ahead forecasting case," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1702-1716, December.
    7. 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.
    8. Binh Do & Robert Faff, 2010. "Does Simple Pairs Trading Still Work?," Financial Analysts Journal, Taylor & Francis Journals, vol. 66(4), pages 83-95, July.
    9. 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.
    10. 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.
    11. Krauss, Christopher & Stübinger, Johannes, 2015. "Nonlinear dependence modeling with bivariate copulas: Statistical arbitrage pairs trading on the S&P 100," FAU Discussion Papers in Economics 15/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    12. Jun Liu & Allan Timmermann, 2013. "Optimal Convergence Trade Strategies," The Review of Financial Studies, Society for Financial Studies, vol. 26(4), pages 1048-1086.
    13. 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. Yen-Wu Ti & Tian-Shyr Dai & Kuan-Lun Wang & Hao-Han Chang & You-Jia Sun, 2024. "Improving Cointegration-Based Pairs Trading Strategy with Asymptotic Analyses and Convergence Rate Filters," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2717-2745, November.
    2. 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.
    3. 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.
    4. Sascha Wilkens, 2025. "Pairs trading in the German stock market: is there still life in the old dog?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 39(2), pages 259-297, June.
    5. 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.
    6. 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.
    7. Matthew Clegg & Christopher Krauss, 2018. "Pairs trading with partial cointegration," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 121-138, January.
    8. Tian-Shyr Dai & Yi-Jen Luo & Hao-Han Chang & Chu-Lan Kao & Kuan-Lun Wang & Liang-Chih Liu, 2024. "Asymptotic analyses for trend-stationary pairs trading strategy in high-frequency trading," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1391-1411, November.
    9. Bu, Hui & Chen, Huanghao & Tang, Wenjin & Yen, Jerome & Zheng, Erya, 2026. "Information diffusion through weighted positive causal networks: Evidence from pair-based trading strategy in China," Pacific-Basin Finance Journal, Elsevier, vol. 96(C).
    10. Mar Grande & Florentino Borondo & Juan Carlos Losada & Javier Borondo, 2024. "Anti-Persistent Values of the Hurst Exponent Anticipate Mean Reversion in Pairs Trading: The Cryptocurrencies Market as a Case Study," Mathematics, MDPI, vol. 12(18), pages 1-14, September.
    11. Federico Platania & Francesco Appio & Celina Toscano Hernandez & Imane El Ouadghiri & Jonathan Peillex, 2025. "A multi-objective pair trading strategy: integrating neural networks and cyclical insights for optimal trading performance," Annals of Operations Research, Springer, vol. 346(2), pages 1553-1572, March.
    12. Kezhong Chen & Constantinos Alexiou, 2025. "Cointegration-based pairs trading: identifying and exploiting similar exchange-traded funds," Journal of Asset Management, Palgrave Macmillan, vol. 26(5), pages 464-488, September.
    13. 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.
    14. Mar Grande & Javier Borondo, 2025. "Embedding pairs trading in market networks: a network science approach to portfolio construction," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-11, December.
    15. 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.
    16. Khizar Qureshi & Tauhid Zaman, 2024. "Pairs Trading Using a Novel Graphical Matching Approach," Papers 2403.07998, arXiv.org.
    17. Knoll, Julian & Stübinger, Johannes & Grottke, Michael, 2017. "Exploiting social media with higher-order Factorization Machines: Statistical arbitrage on high-frequency data of the S&P 500," FAU Discussion Papers in Economics 13/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    18. Fenghui Yu & Wai-Ki Ching & Chufang Wu & Jia-Wen Gu, 2023. "Optimal Pairs Trading Strategies: A Stochastic Mean–Variance Approach," Journal of Optimization Theory and Applications, Springer, vol. 196(1), pages 36-55, January.
    19. 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.
    20. Kasper Johansson & Thomas Schmelzer & Stephen Boyd, 2024. "Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization," Papers 2402.08108, arXiv.org.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:eee:finlet:v:93:y:2026:i:c:s154461232600173x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.