IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v433y2015icp107-125.html
   My bibliography  Save this article

Optimal allocation of trend following strategies

Author

Listed:
  • Grebenkov, Denis S.
  • Serror, Jeremy

Abstract

We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.

Suggested Citation

  • Grebenkov, Denis S. & Serror, Jeremy, 2015. "Optimal allocation of trend following strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 107-125.
    • Handle: RePEc:eee:phsmap:v:433:y:2015:i:c:p:107-125
    DOI: 10.1016/j.physa.2015.03.078
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115003404
    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.2015.03.078?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. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169, October.
    3. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
    4. Campbell, John Y. & Viceira, Luis M., 2002. "Strategic Asset Allocation: Portfolio Choice for Long-Term Investors," OUP Catalogue, Oxford University Press, number 9780198296942.
    5. Clare, Andrew & Seaton, James & Smith, Peter N. & Thomas, Stephen, 2016. "The trend is our friend: Risk parity, momentum and trend following in global asset allocation," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 63-80.
    6. anonymous, 1999. "CRA-qualified investments : two new instruments," Banking and Community Perspectives, Federal Reserve Bank of Dallas, issue 1, pages 1-4,10.
    7. anonymous, 1999. "Southern suitors: wooing foreign investment," EconSouth, Federal Reserve Bank of Atlanta, vol. 1(Q2), pages 8-12.
    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. Sebastien Valeyre, 2022. "Optimal trend following portfolios," Papers 2201.06635, arXiv.org.

    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. Denis S. Grebenkov & Jeremy Serror, 2014. "Optimal Allocation of Trend Following Strategies," Papers 1410.8409, arXiv.org.
    2. Sebastien Valeyre, 2022. "Optimal trend following portfolios," Papers 2201.06635, arXiv.org.
    3. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "On the optimal allocation of assets in investment portfolio with application of modern portfolio and nonlinear dynamic chaos theories in investment, commercial and central banks," Papers 1301.4881, arXiv.org, revised Feb 2013.
    4. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    5. Gökgöz, Fazıl & Atmaca, Mete Emin, 2017. "Portfolio optimization under lower partial moments in emerging electricity markets: Evidence from Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 437-449.
    6. Zhang, Wei-Guo & Zhang, Xili & Chen, Yunxia, 2011. "Portfolio adjusting optimization with added assets and transaction costs based on credibility measures," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 353-360.
    7. Assaf Almog & Ferry Besamusca & Mel MacMahon & Diego Garlaschelli, 2015. "Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.
    8. Pelizzon, Loriana & Weber, Guglielmo, 2009. "Efficient portfolios when housing needs change over the life cycle," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2110-2121, November.
    9. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    10. Esposito, Federico, 2022. "Demand risk and diversification through international trade," Journal of International Economics, Elsevier, vol. 135(C).
    11. Sujoy Mukerji & Han N. Ozsoylev & Jean‐Marc Tallon, 2023. "Trading Ambiguity: A Tale Of Two Heterogeneities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1127-1164, August.
    12. In, Francis & Kim, Sangbae & Gençay, Ramazan, 2011. "Investment horizon effect on asset allocation between value and growth strategies," Economic Modelling, Elsevier, vol. 28(4), pages 1489-1497, July.
    13. Pištěk, Miroslav & Slanina, František, 2011. "Diversity of scales makes an advantage: The case of the Minority Game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2549-2561.
    14. Lin, Wen-chang & Lu, Jin-ray, 2012. "Risky asset allocation and consumption rule in the presence of background risk and insurance markets," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 150-158.
    15. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    16. Výrost, Tomas & Lyócsa, Štefan & Baumöhl, Eduard, 2019. "Network-based asset allocation strategies," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 516-536.
    17. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    18. Penaranda, Francisco, 2007. "Portfolio choice beyond the traditional approach," LSE Research Online Documents on Economics 24481, London School of Economics and Political Science, LSE Library.
    19. Jakub W. Jurek & Luis M. Viceira, 2011. "Optimal Value and Growth Tilts in Long-Horizon Portfolios," Review of Finance, European Finance Association, vol. 15(1), pages 29-74.
    20. Philippe Jacquinot & Nikolay Sukhomlin, 2010. "A direct formulation of implied volatility in the Black-Scholes model," Post-Print hal-02533014, HAL.

    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:433:y:2015:i:c:p:107-125. 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.