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Mispricing, returns and the quest for parsimony

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  • Rudkin, Wanling

Abstract

In the constant trade-off between accurate modelling of stock returns and maintaining a practical number of risk factors there is clear incentive to prematurely suggest optimal solutions. Contemporary model comparison techniques prompt the revisiting of conclusions, Bayesian techniques being especially helpful to reflect the true role the observed data plays in supporting choice. As the literature enters a period of machine learning, and potential over-fitting, this is a timely reminder to give more heed to the true applicability of any proclamation on improvement in asset pricing fit.

Suggested Citation

  • Rudkin, Wanling, 2020. "Mispricing, returns and the quest for parsimony," Finance Research Letters, Elsevier, vol. 37(C).
    • Handle: RePEc:eee:finlet:v:37:y:2020:i:c:s1544612319303216
    DOI: 10.1016/j.frl.2019.101368
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    References listed on IDEAS

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    1. John Lintner, 1965. "Security Prices, Risk, And Maximal Gains From Diversification," Journal of Finance, American Finance Association, vol. 20(4), pages 587-615, December.
    2. David Hirshleifer & Danling Jiang, 2010. "A Financing-Based Misvaluation Factor and the Cross-Section of Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 23(9), pages 3401-3436.
    3. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    4. 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.
    5. 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.
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    7. Francisco Barillas & Jay Shanken, 2018. "Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 73(2), pages 715-754, April.
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    Cited by:

    1. Fang, Ming & Taylor, Stephen, 2021. "A machine learning based asset pricing factor model comparison on anomaly portfolios," Economics Letters, Elsevier, vol. 204(C).

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    More about this item

    Keywords

    Mispricing; Stock returns; Asset pricing model fit; Factor model selection; Bayesian factor inclusion; Sharpe ratio tests;
    All these keywords.

    JEL classification:

    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

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