IDEAS home Printed from https://ideas.repec.org/a/oup/rfinst/v30y2017i4p1316-1338..html
   My bibliography  Save this article

Which Alpha?

Author

Listed:
  • Francisco Barillas
  • Jay Shanken

Abstract

A common approach to comparing asset pricing models involves a competition in pricing test-asset returns. In contrast, we show that for models with traded factors, when the comparison is framed appropriately in terms of success in pricing both the test-asset and factor returns, the extent to which each model is able to price the factors in the other model is what matters for model comparison. Test assets are irrelevant based on several prominent criteria. For models with nontraded factors, test assets are relevant for model comparison insofar as they are needed to identify factor-mimicking portfolio returns.

Suggested Citation

  • Francisco Barillas & Jay Shanken, 2017. "Which Alpha?," Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1316-1338.
  • Handle: RePEc:oup:rfinst:v:30:y:2017:i:4:p:1316-1338.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/rfs/hhw101
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Michael C. Jensen, 1968. "The Performance Of Mutual Funds In The Period 1945–1964," Journal of Finance, American Finance Association, vol. 23(2), pages 389-416, May.
    2. Hansen, Lars Peter & Jagannathan, Ravi, 1997. "Assessing Specification Errors in Stochastic Discount Factor Models," Journal of Finance, American Finance Association, vol. 52(2), pages 557-590, June.
    3. Raymond Kan & Cesare Robotti & Jay Shanken, 2013. "Pricing Model Performance and the Two‐Pass Cross‐Sectional Regression Methodology," Journal of Finance, American Finance Association, vol. 68(6), pages 2617-2649, December.
    4. Pastor, Lubos & Stambaugh, Robert F., 2002. "Mutual fund performance and seemingly unrelated assets," Journal of Financial Economics, Elsevier, vol. 63(3), pages 315-349, March.
    5. Shanken, Jay, 1985. "Multivariate tests of the zero-beta CAPM," Journal of Financial Economics, Elsevier, vol. 14(3), pages 327-348, September.
    6. Francisco Barillas & Jay Shanken, 2018. "Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 73(2), pages 715-754, April.
    7. Kewei Hou & G. Andrew Karolyi & Bong-Chan Kho, 2011. "What Factors Drive Global Stock Returns?," Review of Financial Studies, Society for Financial Studies, vol. 24(8), pages 2527-2574.
    8. Jobson, J. D. & Korkie, Bob, 1982. "Potential performance and tests of portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 10(4), pages 433-466, December.
    9. Fama, Eugene F., 1996. "Multifactor Portfolio Efficiency and Multifactor Asset Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(4), pages 441-465, December.
    10. Fama, Eugene F., 1998. "Determining the Number of Priced State Variables in the ICAPM," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(2), pages 217-231, June.
    11. Kewei Hou & Chen Xue & Lu Zhang, 2015. "Editor's Choice Digesting Anomalies: An Investment Approach," Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 650-705.
    12. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    13. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    14. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-1152, September.
    15. Doron Avramov & John C. Chao, 2006. "An Exact Bayes Test of Asset Pricing Models with Application to International Markets," The Journal of Business, University of Chicago Press, vol. 79(1), pages 293-324, January.
    16. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    17. Kan, Raymond & Robotti, Cesare, 2008. "Specification tests of asset pricing models using excess returns," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 816-838, December.
    18. Hou, Kewei & Xue, Chen & Zhang, Lu, 2015. "A Comparison of New Factor Models," Working Paper Series 2015-05, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    19. 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. Ball, Ray & Gerakos, Joseph & Linnainmaa, Juhani T. & Nikolaev, Valeri, 2016. "Accruals, cash flows, and operating profitability in the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 28-45.
    2. Lin, Qi, 2017. "Noisy prices and the Fama–French five-factor asset pricing model in China," Emerging Markets Review, Elsevier, vol. 31(C), pages 141-163.
    3. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," Review of Finance, European Finance Association, vol. 33(4), pages 1673-1736.
    4. Guo, Bin & Zhang, Wei & Zhang, Yongjie & Zhang, Han, 2017. "The five-factor asset pricing model tests for the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 84-106.
    5. Alex R. Horenstein, 2017. "Betting Against Alpha," Working Papers 2017-13, University of Miami, Department of Economics.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:oup:rfinst:v:30:y:2017:i:4:p:1316-1338.. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press). General contact details of provider: http://edirc.repec.org/data/sfsssea.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.