Pricing Ability of Four Factor Model using Quantile Regression: Evidences from India


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Authors

  • Prashant Sharma Jaipuria Institute of Management Jaipur
  • Prashant Gupta
  • Anurag Singh

Abstract

With the assumption that the returns are normally distributed with no fat tails, most of the existing studies have used ordinary least square (OLS) method to test the pricing ability of asset pricing models. These assumptions are not valid in numerous cases. Thus, to overcome such problem, the present study tests the pricing ability of Cahart (1997) four factor model using quantile regression which provides superior fitting of pricing factors than the traditional OLS model.  The study uses daily data of Indian firms for period from December 1993 to March 2016. The results of the study reveal that the quantile regression model is having superior fitting across all percentile levels than OLS as it fails to fit these four factors across all percentile levels.  Keywords: asset pricing, Fama-French factor model, quantile regression, Cahart's momentumJEL Classifications: C30, G11, G12

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Author Biography

Prashant Sharma, Jaipuria Institute of Management Jaipur

Assistant Professor (Finance and Accounts)

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Published

2016-10-21

How to Cite

Sharma, P., Gupta, P., & Singh, A. (2016). Pricing Ability of Four Factor Model using Quantile Regression: Evidences from India. International Journal of Economics and Financial Issues, 6(4), 1815–1826. Retrieved from https://econjournals.com/index.php/ijefi/article/view/2997

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