IDEAS home Printed from https://ideas.repec.org/a/kap/fmktpm/v39y2025i2d10.1007_s11408-025-00467-8.html
   My bibliography  Save this article

Pairs trading in the German stock market: is there still life in the old dog?

Author

Listed:
  • Sascha Wilkens

Abstract

The use of statistical arbitrage, particularly pairs trading, is a well-established strategy in financial markets. Approaches to identifying and exploiting relative mispricing range from basic distance measures to complex machine learning techniques. Despite the prominence of the German stock market, in-depth studies remain scarce. This paper conducts the first comprehensive analysis of pairs trading in this market from 2000 to 2023, applying established methods and a novel ensemble approach. The results show that certain strategies achieve average monthly returns of approximately 20 basis points, though transaction costs often erode profitability. Performance improves during periods of market stress, and exposure to systematic risk factors remains limited. Sensitivity analyses confirm robustness and identify enhancements, including sector-specific pairing and alternative spread metrics.

Suggested Citation

  • 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.
  • Handle: RePEc:kap:fmktpm:v:39:y:2025:i:2:d:10.1007_s11408-025-00467-8
    DOI: 10.1007/s11408-025-00467-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11408-025-00467-8
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11408-025-00467-8?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. Sungju Hong & Soosung Hwang, 2023. "In search of pairs using firm fundamentals: is pairs trading profitable?," The European Journal of Finance, Taylor & Francis Journals, vol. 29(5), pages 508-526, March.
    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. 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.
    4. 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.
    5. Jacobs, Heiko & Weber, Martin, 2015. "On the determinants of pairs trading profitability," Journal of Financial Markets, Elsevier, vol. 23(C), pages 75-97.
    6. Ardia, David & Guidotti, Emanuele & Kroencke, Tim A., 2024. "Efficient estimation of bid–ask spreads from open, high, low, and close prices," Journal of Financial Economics, Elsevier, vol. 161(C).
    7. Peter Gomber & Uwe Schweickert & Erik Theissen, 2015. "Liquidity Dynamics in an Electronic Open Limit Order Book: an Event Study Approach," European Financial Management, European Financial Management Association, vol. 21(1), pages 52-78, January.
    8. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    9. repec:bla:jfinan:v:53:y:1998:i:6:p:1839-1885 is not listed on IDEAS
    10. Amihud, Yakov & Mendelson, Haim, 1986. "Asset pricing and the bid-ask spread," Journal of Financial Economics, Elsevier, vol. 17(2), pages 223-249, December.
    11. Thomas Johann & Stefan Scharnowski & Erik Theissen & Christian Westheide & Lukas Zimmermann, 2019. "Liquidity in the German Stock Market," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 443-473, October.
    12. 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.
    13. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    14. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    15. David A. Bowen & Mark C. Hutchinson, 2016. "Pairs trading in the UK equity market: risk and return," The European Journal of Finance, Taylor & Francis Journals, vol. 22(14), pages 1363-1387, November.
    16. 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.
    17. Feifei Li & Tzee-Man Chow & Alex Pickard & Yadwinder Garg, 2019. "Transaction Costs of Factor-Investing Strategies," Financial Analysts Journal, Taylor & Francis Journals, vol. 75(2), pages 62-78, April.
    18. 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.
    19. Ramos-Requena, J.P. & Trinidad-Segovia, J.E. & Sánchez-Granero, M.A., 2017. "Introducing Hurst exponent in pair trading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 39-45.
    20. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    21. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    22. Johannes Stübinger & Benedikt Mangold & Christopher Krauss, 2018. "Statistical arbitrage with vine copulas," Quantitative Finance, Taylor & Francis Journals, vol. 18(11), pages 1831-1849, November.
    23. 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.
    24. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    25. 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.
    26. Masood Tadi & Jiv{r}'i Witzany, 2023. "Copula-Based Trading of Cointegrated Cryptocurrency Pairs," Papers 2305.06961, arXiv.org, revised Jun 2023.
    27. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    28. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    29. Christopher Krauss, 2017. "Statistical Arbitrage Pairs Trading Strategies: Review And Outlook," Journal of Economic Surveys, Wiley Blackwell, vol. 31(2), pages 513-545, April.
    30. Binh Do & Robert Faff, 2010. "Does Simple Pairs Trading Still Work?," Financial Analysts Journal, Taylor & Francis Journals, vol. 66(4), pages 83-95, July.
    31. Lutz Johanning & Marc Becker & Arndt Völkle, 2015. "Transaction Costs for German Institutional Investors: Empirical Evidence from Stock Markets," Journal of Applied Corporate Finance, Morgan Stanley, vol. 27(4), pages 96-104, December.
    32. Bui, Quynh & Ślepaczuk, Robert, 2022. "Applying Hurst Exponent in pair trading strategies on Nasdaq 100 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    33. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    34. Shane A. Corwin & Paul Schultz, 2012. "A Simple Way to Estimate Bid‐Ask Spreads from Daily High and Low Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 719-760, April.
    35. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    36. 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.
    37. Pedro A. C. Saffi & Kari Sigurdsson, 2011. "Price Efficiency and Short Selling," The Review of Financial Studies, Society for Financial Studies, vol. 24(3), pages 821-852.
    38. Joel Hasbrouck, 2009. "Trading Costs and Returns for U.S. Equities: Estimating Effective Costs from Daily Data," Journal of Finance, American Finance Association, vol. 64(3), pages 1445-1477, June.
    39. Liu, Weimin, 2006. "A liquidity-augmented capital asset pricing model," Journal of Financial Economics, Elsevier, vol. 82(3), pages 631-671, December.
    40. He, Fuli & Yarahmadi, Ali & Soleymani, Fazlollah, 2024. "Investigation of multivariate pairs trading under copula approach with mixture distribution," Applied Mathematics and Computation, Elsevier, vol. 472(C).
    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. 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.
    2. Ijaz Ur Rehman & Nurul Shahnaz Mahdzan & Rozaimah Zainudin, 2016. "Is the relationship between macroeconomy and stock market liquidity mutually reinforcing? Evidence from an emerging market," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 9(3), pages 294-316.
    3. 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.
    4. Stereńczak, Szymon & Zaremba, Adam & Umar, Zaghum, 2020. "Is there an illiquidity premium in frontier markets?," Emerging Markets Review, Elsevier, vol. 42(C).
    5. Karstanje, Dennis & Sojli, Elvira & Tham, Wing Wah & van der Wel, Michel, 2013. "Economic valuation of liquidity timing," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5073-5087.
    6. Belkhir, Mohamed & Saad, Mohsen & Samet, Anis, 2020. "Stock extreme illiquidity and the cost of capital," Journal of Banking & Finance, Elsevier, vol. 112(C).
    7. Liu, Weimin & Luo, Di & Zhao, Huainan, 2016. "Transaction costs, liquidity risk, and the CCAPM," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 126-145.
    8. Sean A. Anthonisz & Tālis J. Putniņš, 2017. "Asset Pricing with Downside Liquidity Risks," Management Science, INFORMS, vol. 63(8), pages 2549-2572, August.
    9. Chen, Jiaqi & Sherif, Mohamed, 2016. "Illiquidity premium and expected stock returns in the UK: A new approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 52-66.
    10. Ma, Xiuli & Zhang, Xindong & Liu, Weimin, 2021. "Further tests of asset pricing models: Liquidity risk matters," Economic Modelling, Elsevier, vol. 95(C), pages 255-273.
    11. Jacobs, Heiko, 2015. "What explains the dynamics of 100 anomalies?," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 65-85.
    12. Kim, Soonho & Na, Haejung, 2018. "Higher-moment liquidity risks and the cross-section of stock returns," Journal of Financial Markets, Elsevier, vol. 38(C), pages 39-59.
    13. 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.
    14. 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.
    15. Qingjing Zhang & Taufiq Choudhry & Jing-Ming Kuo & Xiaoquan Liu, 2021. "Does liquidity drive stock market returns? The role of investor risk aversion," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 929-958, October.
    16. Kim, Soon-Ho & Lee, Kuan-Hui, 2014. "Pricing of liquidity risks: Evidence from multiple liquidity measures," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 112-133.
    17. Anton Astakhov & Tomas Havranek & Jiri Novak, 2019. "Firm Size And Stock Returns: A Quantitative Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 33(5), pages 1463-1492, December.
    18. Bazgour, Tarik & Heuchenne, Cedric & Sougné, Danielle, 2016. "Conditional portfolio allocation: Does aggregate market liquidity matter?," Journal of Empirical Finance, Elsevier, vol. 35(C), pages 110-135.
    19. Chen, Xiaoyu & Chiang, Thomas C., 2016. "Stock returns and economic forces—An empirical investigation of Chinese markets," Global Finance Journal, Elsevier, vol. 30(C), pages 45-65.
    20. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:kap:fmktpm:v:39:y:2025:i:2:d:10.1007_s11408-025-00467-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.