IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v488y2017icp39-45.html
   My bibliography  Save this article

Introducing Hurst exponent in pair trading

Author

Listed:
  • Ramos-Requena, J.P.
  • Trinidad-Segovia, J.E.
  • Sánchez-Granero, M.A.

Abstract

In this paper we introduce a new methodology for pair trading. This new method is based on the calculation of the Hurst exponent of a pair. Our approach is inspired by the classical concepts of co-integration and mean reversion but joined under a unique strategy. We will show how Hurst approach presents better results than classical Distance Method and Correlation strategies in different scenarios. Results obtained prove that this new methodology is consistent and suitable by reducing the drawdown of trading over the classical ones getting as a result a better performance.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:488:y:2017:i:c:p:39-45
    DOI: 10.1016/j.physa.2017.06.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117306738
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2017.06.032?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Trinidad Segovia, J.E., 2013. "Measuring the self-similarity exponent in Lévy stable processes of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5330-5345.
    2. Mark Mitchell & Todd Pulvino, 2001. "Characteristics of Risk and Return in Risk Arbitrage," Journal of Finance, American Finance Association, vol. 56(6), pages 2135-2175, December.
    3. 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.
    4. Barunik, Jozef & Kristoufek, Ladislav, 2010. "On Hurst exponent estimation under heavy-tailed distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(18), pages 3844-3855.
    5. Di Matteo, T. & Aste, T. & Dacorogna, M.M., 2003. "Scaling behaviors in differently developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 183-188.
    6. Wing Hong Chan & Ranjini Jha & Madhu Kalimipalli, 2009. "The Economic Value Of Using Realized Volatility In Forecasting Future Implied Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 32(3), pages 231-259, September.
    7. Engle, Robert & Granger, Clive, 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.
    8. Weron, Rafał, 2002. "Estimating long-range dependence: finite sample properties and confidence intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 285-299.
    9. Grundy, Bruce D & Martin, J Spencer, 2001. "Understanding the Nature of the Risks and the," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 29-78.
    10. David K. Backus & Stanley E. Zin, 1993. "Long-memory inflation uncertainty: evidence from the term structure of interest rates," Proceedings, Federal Reserve Bank of Cleveland, pages 681-708.
    11. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    12. 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.
    13. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    14. Shea, Gary S, 1991. "Uncertainty and Implied Variance Bounds in Long-Memory Models of the Interest Rate Term Structure," Empirical Economics, Springer, vol. 16(3), pages 287-312.
    15. Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
    16. Denis Conniffe & John E. Spencer, 2000. "Approximating the Distribution of the R/s Statistic," The Economic and Social Review, Economic and Social Studies, vol. 31(3), pages 237-248.
    17. John Haslett & Adrian E. Raftery, 1989. "Space‐Time Modelling with Long‐Memory Dependence: Assessing Ireland's Wind Power Resource," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(1), pages 1-21, March.
    18. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    19. repec:bla:jfinan:v:59:y:2004:i:3:p:1039-1082 is not listed on IDEAS
    20. Couillard, Michel & Davison, Matt, 2005. "A comment on measuring the Hurst exponent of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 404-418.
    21. Robert Elliott & John Van Der Hoek & William Malcolm, 2005. "Pairs trading," Quantitative Finance, Taylor & Francis Journals, vol. 5(3), pages 271-276.
    22. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 189-209, September.
    23. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    24. Sánchez Granero, M.A. & Trinidad Segovia, J.E. & García Pérez, J., 2008. "Some comments on Hurst exponent and the long memory processes on capital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5543-5551.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Po-Keng Cheng, 2020. "Listen to the Signals from an Interactive Agent-Based Model," Working Papers hal-02982908, HAL.
    2. Matthieu Garcin, 2019. "Hurst Exponents And Delampertized Fractional Brownian Motions," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-26, August.
    3. Samuel T. Ogunjo, 2023. "The impact of the 2007–2008 global financial crisis on the multifractality of the Nigerian Stock Exchange," SN Business & Economics, Springer, vol. 3(1), pages 1-17, January.
    4. 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.
    5. Estefanía Montoya-Cruz & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "Exploring Arbitrage Strategies in Corporate Social Responsibility Companies," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    6. Gómez-Águila, A. & Sánchez-Granero, M.A., 2021. "A theoretical framework for the TTA algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    7. Lifeng Wu & Xiaohui Gao & Yan Chen, 2019. "Memory Property of Grey Accumulation Generation Sequence," Complexity, Hindawi, vol. 2019, pages 1-10, July.
    8. Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    9. Bikramaditya Ghosh & Spyros Papathanasiou & Dimitrios Kenourgios, 2022. "Cross-Country Linkages and Asymmetries of Sovereign Risk Pluralistic Investigation of CDS Spreads," Sustainability, MDPI, vol. 14(21), pages 1-10, October.
    10. Vladimír Holý & Michal Černý, 2022. "Bertram’s pairs trading strategy with bounded risk," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 667-682, June.
    11. 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).
    12. Gupta, Kartikay & Chatterjee, Niladri, 2020. "Selecting stock pairs for pairs trading while incorporating lead–lag relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    13. Matthieu Garcin, 2018. "Hurst exponents and delampertized fractional Brownian motions," Working Papers hal-01919754, HAL.
    14. Lotfalinezhad, Hamze & Maleki, Ali, 2020. "TTA, a new approach to estimate Hurst exponent with less estimation error and computational time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    15. José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "An Alternative Approach to Measure Co-Movement between Two Time Series," Mathematics, MDPI, vol. 8(2), pages 1-24, February.
    16. 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.
    17. Poitras, Geoffrey, 2018. "The pre-history of econophysics and the history of economics: Boltzmann versus the marginalists," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 89-98.
    18. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
    19. Lucas Schneider & Johannes Stübinger, 2020. "Dispersion Trading Based on the Explanatory Power of S&P 500 Stock Returns," Mathematics, MDPI, vol. 8(9), pages 1-22, September.

    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. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    2. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Trinidad Segovia, J.E., 2013. "Measuring the self-similarity exponent in Lévy stable processes of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5330-5345.
    3. López-García, M.N. & Trinidad-Segovia, J.E. & Sánchez-Granero, M.A. & Pouchkarev, I., 2021. "Extending the Fama and French model with a long term memory factor," European Journal of Operational Research, Elsevier, vol. 291(2), pages 421-426.
    4. José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "An Alternative Approach to Measure Co-Movement between Two Time Series," Mathematics, MDPI, vol. 8(2), pages 1-24, February.
    5. Sánchez Granero, M.A. & Trinidad Segovia, J.E. & García Pérez, J., 2008. "Some comments on Hurst exponent and the long memory processes on capital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5543-5551.
    6. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    7. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
    8. Ladislav Kristoufek & Miloslav Vosvrda, 2014. "Measuring capital market efficiency: long-term memory, fractal dimension and approximate entropy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(7), pages 1-9, July.
    9. Auer, Benjamin R., 2016. "On time-varying predictability of emerging stock market returns," Emerging Markets Review, Elsevier, vol. 27(C), pages 1-13.
    10. Trinidad Segovia, J.E. & Fernández-Martínez, M. & Sánchez-Granero, M.A., 2019. "A novel approach to detect volatility clusters in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    11. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    12. Corzo Santamaría, Teresa & Martin-Bujack, Karin & Portela, Jose & Sáenz-Diez, Rocio, 2022. "Early market efficiency testing among hydrogen players," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 723-742.
    13. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    14. Chong, Terence Tai-Leung, 2000. "Estimating the differencing parameter via the partial autocorrelation function," Journal of Econometrics, Elsevier, vol. 97(2), pages 365-381, August.
    15. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    16. Liu, Jian & Cheng, Cheng & Yang, Xianglin & Yan, Lizhao & Lai, Yongzeng, 2019. "Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    17. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
    18. Ma, Pengcheng & Li, Daye & Li, Shuo, 2016. "Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 163-176.
    19. Kristoufek, Ladislav, 2014. "Leverage effect in energy futures," Energy Economics, Elsevier, vol. 45(C), pages 1-9.
    20. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.

    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:phsmap:v:488:y:2017:i:c:p:39-45. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.