IDEAS home Printed from https://ideas.repec.org/a/bla/irvfin/v16y2016i2p307-319.html
   My bibliography  Save this article

Statistical Arbitrage with Pairs Trading

Author

Listed:
  • Ahmet Göncü
  • Erdinç Akyıldırım

Abstract

No abstract is available for this item.

Suggested Citation

  • Ahmet Göncü & Erdinç Akyıldırım, 2016. "Statistical Arbitrage with Pairs Trading," International Review of Finance, International Review of Finance Ltd., vol. 16(2), pages 307-319, June.
  • Handle: RePEc:bla:irvfin:v:16:y:2016:i:2:p:307-319
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/irfi.12074
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. 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.
    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. Nicolas Huck & Komivi Afawubo, 2015. "Pairs trading and selection methods: is cointegration superior?," Applied Economics, Taylor & Francis Journals, vol. 47(6), pages 599-613, February.
    4. 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.
    5. Zhengqin Zeng & Chi-Guhn Lee, 2014. "Pairs trading: optimal thresholds and profitability," Quantitative Finance, Taylor & Francis Journals, vol. 14(11), pages 1881-1893, November.
    6. Hogan, Steve & Jarrow, Robert & Teo, Melvyn & Warachka, Mitch, 2004. "Testing market efficiency using statistical arbitrage with applications to momentum and value strategies," Journal of Financial Economics, Elsevier, vol. 73(3), pages 525-565, September.
    7. Nicolas Huck & Komivi Afawubo, 2015. "Pairs trading and selection methods: is cointegration superior?," Post-Print hal-01369852, HAL.
    8. Marco Avellaneda & Jeong-Hyun Lee, 2010. "Statistical arbitrage in the US equities market," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 761-782.
    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. 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.
    2. 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.
    3. Alexander Lipton & Marcos Lopez de Prado, 2020. "A closed-form solution for optimal mean-reverting trading strategies," Papers 2003.10502, arXiv.org.
    4. Endres, Sylvia & Stübinger, Johannes, 2018. "A flexible regime switching model with pairs trading application to the S&P 500 high-frequency stock returns," FAU Discussion Papers in Economics 07/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    5. 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.

    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. Alexander Lipton & Marcos Lopez de Prado, 2020. "A closed-form solution for optimal mean-reverting trading strategies," Papers 2003.10502, arXiv.org.
    2. 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.
    3. Ahmet Göncü & Erdinc Akyildirim, 2016. "A stochastic model for commodity pairs trading," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1843-1857, December.
    4. 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.
    5. Erdinc Akyildirim & Ahmet Goncu & Alper Hekimoglu & Duc Khuong Nguyen & Ahmet Sensoy, 2023. "Statistical arbitrage: factor investing approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(4), pages 1295-1331, December.
    6. Khizar Qureshi & Tauhid Zaman, 2024. "Pairs Trading Using a Novel Graphical Matching Approach," Papers 2403.07998, arXiv.org.
    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. 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.
    9. Boming Ning & Prakash Chakraborty & Kiseop Lee, 2023. "Optimal Entry and Exit with Signature in Statistical Arbitrage," Papers 2309.16008, arXiv.org, revised Mar 2024.
    10. 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 Jul 2022.
    11. 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.
    12. 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.
    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. Sánchez-Granero, M.A. & Balladares, K.A. & Ramos-Requena, J.P. & Trinidad-Segovia, J.E., 2020. "Testing the efficient market hypothesis in Latin American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    15. Stübinger, Johannes, 2018. "Statistical arbitrage with optimal causal paths on high-frequencydata of the S&P 500," FAU Discussion Papers in Economics 01/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    16. Tim Leung & Kevin W. Lu, 2023. "Monte Carlo Simulation for Trading Under a L\'evy-Driven Mean-Reverting Framework," Papers 2309.05512, arXiv.org, revised Jan 2024.
    17. Marianna Brunetti & Roberta De Luca, 2021. "Pairs Trading In The Index Options Market," CEIS Research Paper 512, Tor Vergata University, CEIS, revised 02 Sep 2021.
    18. 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.
    19. Weiguang Han & Boyi Zhang & Qianqian Xie & Min Peng & Yanzhao Lai & Jimin Huang, 2023. "Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning," Papers 2301.10724, arXiv.org, revised Feb 2023.
    20. Bo Liu & Lo-Bin Chang & Hélyette Geman, 2017. "Intraday pairs trading strategies on high frequency data: the case of oil companies," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 87-100, January.

    More about this item

    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:bla:irvfin:v:16:y:2016:i:2:p:307-319. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1369-412X .

    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.