IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/8308.html
   My bibliography  Save this paper

Evaluation of pairs trading strategy at the Brazilian financial market

Author

Abstract

Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. The idea is simple: find two stocks that move together and take long/short positions when they diverge abnormally, hoping that the prices will converge in the future. From the academic point of view of weak market efficiency theory, pairs trading strategy shouldn’t present positive performance since, according to it, the actual price of a stock reflects its past trading data, including historical prices. This leaves us with a question, does pairs trading strategy presents positive performance for the Brazilian market? The main objective of this research is to verify the performance and risk of pairs trading in the Brazilian financial market for different frequencies of the database, daily, weekly and monthly prices for the same time period. The main conclusion of this simulation is that pairs trading strategy was a profitable and market neutral strategy at the Brazilian Market. Such profitability was consistent over a region of the strategy’s parameters. The best results were found for the highest frequency (daily), which is an intuitive result.

Suggested Citation

  • Perlin, M., 2007. "Evaluation of pairs trading strategy at the Brazilian financial market," MPRA Paper 8308, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:8308
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/8308/1/MPRA_paper_8308.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero & Maria Dolores Garcia-Artiles, 1997. "Using nearest neighbour predictors to forecast the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 21(1), pages 75-91, January.
    2. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability of Technical Analysis: A Review," AgMAS Project Research Reports 37487, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    3. Dueker, Michael & Neely, Christopher J., 2007. "Can Markov switching models predict excess foreign exchange returns?," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 279-296, February.
    4. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    5. 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.
    6. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    7. French, Kenneth R., 1980. "Stock returns and the weekend effect," Journal of Financial Economics, Elsevier, vol. 8(1), pages 55-69, March.
    8. repec:bla:eufman:v:4:y:1998:i:1:p:91-103 is not listed on IDEAS
    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. Alessia Naccarato & Andrea Pierini & Giovanna Ferraro, 2021. "Markowitz portfolio optimization through pairs trading cointegrated strategy in long-term investment," Annals of Operations Research, Springer, vol. 299(1), pages 81-99, April.
    2. Perlin, M., 2007. "M of a kind: A Multivariate Approach at Pairs Trading," MPRA Paper 8309, University Library of Munich, Germany.
    3. Masood Tadi & Irina Kortchmeski, 2021. "Evaluation of Dynamic Cointegration-Based Pairs Trading Strategy in the Cryptocurrency Market," Papers 2109.10662, arXiv.org.
    4. Fabio Pizzutilo, 2013. "A Note on the Effectiveness of Pairs Trading For Individual Investors," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 763-771.
    5. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2017. "Searching for Inefficiencies in Exchange Rate Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 405-432, March.
    6. 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].
    7. Sayat R. Baronyan & İ. İlkay Boduroğlu & Emrah Şener, 2010. "Investigation Of Stochastic Pairs Trading Strategies Under Different Volatility Regimes," Manchester School, University of Manchester, vol. 78(s1), pages 114-134, September.
    8. R. Todd Smith & Xun Xu, 2017. "A good pair: alternative pairs-trading strategies," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(1), pages 1-26, February.
    9. 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.
    10. 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.
    11. Bolgun, Evren & Kurun, Engin & Guven, Serhat, 2009. "Dynamic Pairs Trading Strategy For The Companies Listed In The Istanbul Stock Exchange," MPRA Paper 19887, University Library of Munich, Germany.
    12. Laila Taskeen Qazi & Atta Ur Rahman & Saleem Gul, 2015. "Which Pairs of Stocks should we Trade? Selection of Pairs for Statistical Arbitrage and Pairs Trading in Karachi Stock Exchange," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 54(3), pages 215-244.
    13. 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.
    14. 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.
    15. 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.
    16. Lei, Yaoting & Xu, Jing, 2015. "Costly arbitrage through pairs trading," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 1-19.
    17. Geetu Aggarwal & Navdeep Aggarwal, 2021. "Risk-adjusted Returns from Statistical Arbitrage Opportunities in Indian Stock Futures Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(1), pages 79-99, March.
    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. Andreas Mikkelsen, 2018. "Pairs trading: the case of Norwegian seafood companies," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 303-318, January.
    20. 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.

    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. Perlin, M., 2007. "M of a kind: A Multivariate Approach at Pairs Trading," MPRA Paper 8309, University Library of Munich, Germany.
    2. Qianwei Ying & Tahir Yousaf & Qurat ul Ain & Yasmeen Akhtar & Muhammad Shahid Rasheed, 2019. "Stock Investment and Excess Returns: A Critical Review in the Light of the Efficient Market Hypothesis," JRFM, MDPI, vol. 12(2), pages 1-22, June.
    3. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    4. Bartram, Söhnke M. & Grinblatt, Mark, 2018. "Agnostic fundamental analysis works," Journal of Financial Economics, Elsevier, vol. 128(1), pages 125-147.
    5. Trabelsi, Mohamed Ali, 2010. "Choix de portefeuille: comparaison des différentes stratégies [Portfolio selection: comparison of different strategies]," MPRA Paper 82946, University Library of Munich, Germany, revised 01 Dec 2010.
    6. Zhao, Ruwei, 2020. "Quantifying the cross sectional relation of daily happiness sentiment and return skewness: Evidence from US industries," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    7. Christiane Goodfellow & Dirk Schiereck & Steffen Wippler, 2013. "Are behavioural finance equity funds a superior investment? A note on fund performance and market efficiency," Journal of Asset Management, Palgrave Macmillan, vol. 14(2), pages 111-119, April.
    8. David Peón & Anxo Calvo, 2012. "Using Behavioral Economics to Analyze Credit Policies in the Banking Industry," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 145-160.
    9. repec:dau:papers:123456789/2514 is not listed on IDEAS
    10. ATM Adnan, 2018. "Home vs. Cross-Border Takeovers: Is There Any Difference in Investor Perception?," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2018(2), pages 59-84.
    11. Roberto Casarin & Andrea Piva & Loriana Pelizzon, 2008. "Italian Equity Funds: Efficiency and Performance Persistence," The IUP Journal of Financial Economics, IUP Publications, vol. 0(1), pages 7-28, March.
    12. Samiran Jana, 2016. "Effect of Investors’ Sentiment on Indian Stock Market," Global Business Review, International Management Institute, vol. 17(5), pages 1240-1249, October.
    13. Day, Min-Yuh & Ni, Yensen, 2023. "The profitability of seasonal trading timing: Insights from energy-related markets," Energy Economics, Elsevier, vol. 128(C).
    14. Fernando Rubio, 2005. "Estrategias Cuantitativas De Valor Y Retornos Por Accion De Largo," Finance 0503029, University Library of Munich, Germany.
    15. Neszveda, Gábor & Vágó, Ákos, 2021. "A likviditásnyújtás kereskedési stratégiájának hozamvizsgálata a magyar részvénypiacon [Examining trade-strategy results of liquidity provision on the Hungarian stock market]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 794-814.
    16. Lyon, Thomas & Lu, Yao & Shi, Xinzheng & Yin, Qie, 2013. "How do investors respond to Green Company Awards in China?," Ecological Economics, Elsevier, vol. 94(C), pages 1-8.
    17. Lu Zhang, 2019. "Q-factors and Investment CAPM," NBER Working Papers 26538, National Bureau of Economic Research, Inc.
    18. Adam Karp & Gary Van Vuuren, 2019. "Investment Implications Of The Fractal Market Hypothesis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 1-27, March.
    19. García Iborra, Rafael & Howden, David, 2016. "Uses and Misuses of Arbitrage in Financial Theory, and a Suggested Alternative," MPRA Paper 79802, University Library of Munich, Germany.
    20. Erica X. N. Li & Dmitry Livdan & Lu Zhang, 2009. "Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4301-4334, November.
    21. Benjamin R. Auer, 2019. "Does the strength of capital market anomalies exhibit seasonal patterns?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 91-103, January.

    More about this item

    Keywords

    pairs trading; quantitative strategy; asset allocation;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:pra:mprapa:8308. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.