IDEAS home Printed from https://ideas.repec.org/p/war/wpaper/2025-20.html
   My bibliography  Save this paper

Performance of Pairs Trading Strategies Based on Renko and Kagi Charts

Author

Listed:
  • Yufei Sun

    (Faculty of Economic Sciences, University of Warsaw)

Abstract

This paper investigates the profitability and robustness of pairs trading strategies based on non-parametric technical chart constructions—Renko and Kagi—across the U.S. and Chinese equity markets. Within a market-neutral, mean-reversion framework, the study examines strategy performance under varying market regimes, including the Global Financial Crisis (GFC) and the COVID-19 period. Using historical data from indices such as the S&P 500 and the CSI series, pairs are selected via statistical patterns in Renko and Kagi charts. Robustness checks consider varying trading horizons, the number of pairs, and transaction costs. Results show that both chart-based strategies generate significant excess returns and exhibit strong Sharpe ratios before costs. While trading frictions reduce profitability, Renko-based strategies remain resilient, especially during crises. The findings highlight that adaptive and non-parametric charting methods can effectively capture transient mispricings and provide viable alternatives for statistical arbitrage in turbulent markets.

Suggested Citation

  • Yufei Sun, 2025. "Performance of Pairs Trading Strategies Based on Renko and Kagi Charts," Working Papers 2025-20, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2025-20
    as

    Download full text from publisher

    File URL: https://www.wne.uw.edu.pl/download_file/6099/0
    File Function: First version, 2025
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Timofei Bogomolov, 2013. "Pairs trading based on statistical variability of the spread process," Quantitative Finance, Taylor & Francis Journals, vol. 13(9), pages 1411-1430, September.
    4. Ping Wu & Robert J. Elliott, 2005. "Parameter Estimation For A Regime-Switching Mean-Reverting Model With Jumps," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(06), pages 791-806.
    5. Martin Eling, 2008. "Does the Measure Matter in the Mutual Fund Industry?," Financial Analysts Journal, Taylor & Francis Journals, vol. 64(3), pages 54-66, May.
    6. S. Endres & J. Stübinger, 2019. "Optimal trading strategies for Lévy-driven Ornstein–Uhlenbeck processes," Applied Economics, Taylor & Francis Journals, vol. 51(29), pages 3153-3169, June.
    7. Engle, R. F. & Granger, C. W. J. (ed.), 1991. "Long-Run Economic Relationships: Readings in Cointegration," OUP Catalogue, Oxford University Press, number 9780198283393.
    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.
    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. 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].
    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. 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.
    4. Hanxiong Zhang & Andrew Urquhart, 2020. "Do momentum and reversal strategies work in commodity futures? A comprehensive study," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 12(4), pages 375-409, April.
    5. Masood Tadi & Jiří Witzany, 2025. "Copula-based trading of cointegrated cryptocurrency Pairs," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-32, December.
    6. Xiang, Yun & He, Jiaxuan, 2022. "Pairs trading and asset pricing," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    7. Tim Leung & Kevin W. Lu, 2023. "Monte Carlo Simulation for Trading Under a Lévy-Driven Mean-Reverting Framework," Applied Mathematical Finance, Taylor & Francis Journals, vol. 30(4), pages 207-230, July.
    8. Krauss, Christopher & Krüger, Tom & Beerstecher, Daniel, 2015. "The Piotroski F-Score: A fundamental value strategy revisited from an investor's perspective," FAU Discussion Papers in Economics 13/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    9. Krauss, Christopher & Beerstecher, Daniel & Krüger, Tom, 2015. "Feasible earnings momentum in the U.S. stock market: An investor's perspective," FAU Discussion Papers in Economics 12/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    10. 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.
    11. Johannes Stübinger & Sylvia Endres, 2018. "Pairs trading with a mean-reverting jump–diffusion model on high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 18(10), pages 1735-1751, October.
    12. Endres, Sylvia & Stübinger, Johannes, 2017. "Optimal trading strategies for Lévy-driven Ornstein-Uhlenbeck processes," FAU Discussion Papers in Economics 17/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    13. 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.
    14. 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.
    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. 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 Oct 2025.
    17. 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.
    18. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    19. 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.
    20. 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.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:war:wpaper:2025-20. 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: Jacek Rapacz (email available below). General contact details of provider: https://edirc.repec.org/data/fesuwpl.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.