IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v32y2016i2p548-558.html
   My bibliography  Save this article

Betas and the myth of market neutrality

Author

Listed:
  • Papageorgiou, Nicolas
  • Reeves, Jonathan J.
  • Xie, Xuan

Abstract

Market neutral funds are commonly advertised as alternative investments that offer returns which are uncorrelated with the broad market. Utilizing recent advances in financial econometrics, we demonstrate that using standard forecasting methods to construct market (beta) neutral funds is often very inaccurate. Our findings demonstrate that the econometric methods that are commonly employed for forecasting the beta (systematic) risk typically lack sufficient accuracy to permit the successful construction of market neutral portfolios. The results in this paper also highlight the need for higher frequency returns data to be utilized more commonly. Using daily returns over the past year, we demonstrate an approach that is easy to implement and delivers a substantial improvement, relative to other methods, when attempting to construct a market neutral portfolio.

Suggested Citation

  • Papageorgiou, Nicolas & Reeves, Jonathan J. & Xie, Xuan, 2016. "Betas and the myth of market neutrality," International Journal of Forecasting, Elsevier, vol. 32(2), pages 548-558.
  • Handle: RePEc:eee:intfor:v:32:y:2016:i:2:p:548-558
    DOI: 10.1016/j.ijforecast.2015.09.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207015001533
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijforecast.2015.09.005?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. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa Onur, 2011. "Do hedge funds' exposures to risk factors predict their future returns?," Journal of Financial Economics, Elsevier, vol. 101(1), pages 36-68, July.
    2. Andrew J. Patton, 2009. "Are "Market Neutral" Hedge Funds Really Market Neutral?," Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2295-2330, July.
    3. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics," Econometrica, Econometric Society, vol. 72(3), pages 885-925, May.
    4. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa Onur, 2012. "Systematic risk and the cross section of hedge fund returns," Journal of Financial Economics, Elsevier, vol. 106(1), pages 114-131.
    5. Stephen J. Brown & Greg N. Gregoriou & Razvan Pascalau, 2012. "Diversification in Funds of Hedge Funds: Is It Possible to Overdiversify?," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 2(1), pages 89-110.
    6. Eric Ghysels, 1998. "On Stable Factor Structures in the Pricing of Risk: Do Time-Varying Betas Help or Hurt?," Journal of Finance, American Finance Association, vol. 53(2), pages 549-573, April.
    7. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    8. Stephen J. Brown, 2011. "The efficient markets hypothesis: The demise of the demon of chance?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 51(1), pages 79-95, March.
    9. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    10. Brandon Chen & Jonathan J. Reeves, 2012. "Dynamic asset beta measurement," Applied Financial Economics, Taylor & Francis Journals, vol. 22(19), pages 1655-1664, October.
    11. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    12. Grundy, Bruce D & Martin, J Spencer, 2001. "Understanding the Nature of the Risks and the," Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 29-78.
    13. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    14. Novy-Marx, Robert, 2012. "Is momentum really momentum?," Journal of Financial Economics, Elsevier, vol. 103(3), pages 429-453.
    15. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    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. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    2. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    3. Doan, Bao & Lee, John B. & Liu, Qianqiu & Reeves, Jonathan J., 2022. "Beta measurement with high frequency returns," Finance Research Letters, Elsevier, vol. 47(PA).
    4. Cenesizoglu, Tolga & de Oliveira Ferrazoli Ribeiro, Fabio & Reeves, Jonathan J., 2017. "Beta forecasting at long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 936-957.

    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. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa O., 2014. "Macroeconomic risk and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 114(1), pages 1-19.
    2. Zaremba, Adam & Czapkiewicz, Anna, 2017. "The cross section of international government bond returns," Economic Modelling, Elsevier, vol. 66(C), pages 171-183.
    3. Agarwal, Vikas & Green, T. Clifton & Ren, Honglin, 2018. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," Journal of Financial Economics, Elsevier, vol. 127(3), pages 417-434.
    4. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    5. Stafylas, Dimitrios & Anderson, Keith & Uddin, Moshfique, 2017. "Recent advances in explaining hedge fund returns: Implicit factors and exposures," Global Finance Journal, Elsevier, vol. 33(C), pages 69-87.
    6. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    7. Agarwal, Vikas & Green, Tracy Clifton & Ren, Honglin, 2017. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," CFR Working Papers 15-08, University of Cologne, Centre for Financial Research (CFR), revised 2017.
    8. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    9. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa O., 2019. "Upside potential of hedge funds as a predictor of future performance," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 212-229.
    10. Mark Grinblatt & Tobias J. Moskowitz, 2002. "What Do We Really Know About the Cross-Sectional Relation Between Past and Expected Returns?," NBER Working Papers 8744, National Bureau of Economic Research, Inc.
    11. Anh Duy Nguyen, 2020. "Alternative reversal variable," Post-Print hal-02388743, HAL.
    12. Israel, Ronen & Moskowitz, Tobias J., 2013. "The role of shorting, firm size, and time on market anomalies," Journal of Financial Economics, Elsevier, vol. 108(2), pages 275-301.
    13. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
    14. Mao, Mike Qinghao & Wei, K.C. John, 2014. "Price and earnings momentum: An explanation using return decomposition," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 332-351.
    15. Sina Ehsani & Juhani T. Linnainmaa, 2019. "Factor Momentum and the Momentum Factor," NBER Working Papers 25551, National Bureau of Economic Research, Inc.
    16. Mustafa Onur Caglayan & Sevan Ulutas, 2014. "Emerging Market Exposures and the Predictability of Hedge Fund Returns," Financial Management, Financial Management Association International, vol. 43(1), pages 149-180, March.
    17. Cooper, Michael J. & Gubellini, Stefano, 2011. "The critical role of conditioning information in determining if value is really riskier than growth," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 289-305, March.
    18. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets," Econometrica, Econometric Society, vol. 84, pages 985-1046, May.
    19. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    20. Anh Duy Nguyen, 2019. "Alternative reversal variable," Working Papers hal-02388743, 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:intfor:v:32:y:2016:i:2:p:548-558. 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.elsevier.com/locate/ijforecast .

    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.