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Data Envelopment Analysis and Multifactor Asset Pricing Models

Author

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  • Pablo Solórzano-Taborga

    (Department of Business Administration, Rey Juan Carlos University, 28032 Madrid, Spain)

  • Ana Belén Alonso-Conde

    (Department of Business Administration, Rey Juan Carlos University, 28032 Madrid, Spain)

  • Javier Rojo-Suárez

    (Department of Business Administration, Rey Juan Carlos University, 28032 Madrid, Spain)

Abstract

Recent literature shows that market anomalies have significantly diminished, while research on market factors has largely improved the performance of asset pricing models. In this paper we study the extent to which data envelopment analysis (DEA) techniques can help improve the performance of multifactor models. Specifically, we test the explanatory power of the Fama and French three-factor model, combined with an additional factor based on DEA, on a sample of 2101 European equity funds, for the period from 2001 to 2016. Accordingly, we first form the fund portfolios that constitute our test assets and create the efficiency factor. Secondly, we estimate the prices of risk tied to the four factors using ordinary least squares (OLS) on a two-stage cross-sectional regression. Finally, we use the R-squared statistic estimated by generalized least squares (GLS), as well as the Gibbons Ross and Shanken test and the J -test for overidentifying restrictions in order to study the performance of the model, including and omitting the efficiency factor. The results show that the efficiency factor improves the performance of the model and reduces the pricing errors of the assets under consideration, which allows us to conclude that the efficiency index may be used as a factor in asset pricing models.

Suggested Citation

  • Pablo Solórzano-Taborga & Ana Belén Alonso-Conde & Javier Rojo-Suárez, 2020. "Data Envelopment Analysis and Multifactor Asset Pricing Models," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    • Handle: RePEc:gam:jijfss:v:8:y:2020:i:2:p:24-:d:347105
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