IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v37y2020ics1544612319303216.html
   My bibliography  Save this article

Mispricing, returns and the quest for parsimony

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612319303216
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2019.101368?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. 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.
    2. Francisco Barillas & Jay Shanken, 2018. "Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 73(2), pages 715-754, April.
    3. John Lintner, 1965. "Security Prices, Risk, And Maximal Gains From Diversification," Journal of Finance, American Finance Association, vol. 20(4), pages 587-615, December.
    4. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    5. 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.
    6. 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.
    7. 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.
    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. Fang, Ming & Taylor, Stephen, 2021. "A machine learning based asset pricing factor model comparison on anomaly portfolios," Economics Letters, Elsevier, vol. 204(C).

    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. Robert F. Stambaugh & Yu Yuan, 2017. "Mispricing Factors," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1270-1315.
    2. Yu Wang & Haicheng Shu, 2019. "Evaluating the Performance of Factor Pricing Models for Different Stock Market Trends: Evidence from China," Working Papers 2019-10-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    3. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1673-1736.
    4. Hanauer, Matthias X. & Lauterbach, Jochim G., 2019. "The cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 38(C), pages 265-286.
    5. Gregory Nazaire & Maria Pacurar & Oumar Sy, 2020. "Betas versus characteristics: A practical perspective," European Financial Management, European Financial Management Association, vol. 26(5), pages 1385-1413, November.
    6. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    7. Chou, Pin-Huang & Ko, Kuan-Cheng & Rhee, S. Ghon, 2023. "Comparing competing factor and characteristics models: Evidence in Japan," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    8. Zhang, Qun & Zhang, Peihui & Liu, Hao, 2023. "Does expected idiosyncratic skewness of firms' profit predict the cross-section of stock returns? Evidence from China," Research in International Business and Finance, Elsevier, vol. 64(C).
    9. Bradrania, Reza & Veron, Jose Francisco & Wu, Winston, 2023. "The beta anomaly and the quality effect in international stock markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    10. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    11. Bradrania, Reza & Veron, Jose Francisco, 2023. "The beta anomaly in the Australian stock market and the lottery demand," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    12. Shi, Huai-Long & Zhou, Wei-Xing, 2021. "Horse race of weekly idiosyncratic momentum strategies with respect to various risk metrics: Evidence from the Chinese stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    13. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2020. "Joint Extreme events in equity returns and liquidity and their cross-sectional pricing implications," Journal of Banking & Finance, Elsevier, vol. 115(C).
    14. González-Sánchez, Mariano, 2022. "Factorial asset pricing models using statistical anomalies," Research in International Business and Finance, Elsevier, vol. 60(C).
    15. Figlioli, Bruno & Lima, Fabiano Guasti, 2019. "Stock pricing in Latin America: The synchronicity effect," Emerging Markets Review, Elsevier, vol. 39(C), pages 1-17.
    16. Azevedo, Vitor, 2023. "Analysts’ underreaction and momentum strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    17. Michael Ungeheuer & Martin Weber, 2021. "The Perception of Dependence, Investment Decisions, and Stock Prices," Journal of Finance, American Finance Association, vol. 76(2), pages 797-844, April.
    18. Zhang, Manqing & Ma, Yao & Yang, Baochen & Fan, Ying, 2024. "The change in salience and the cross-section of stock returns: Empirical evidence from China A-shares," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    19. Mbengue, Mohamed Lamine & Ndiaye, Bara & Sy, Oumar, 2023. "Which factors explain African stock returns?," Finance Research Letters, Elsevier, vol. 54(C).
    20. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).

    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

    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:eee:finlet:v:37:y:2020:i:c:s1544612319303216. 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/frl .

    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.