intrinsicFRP

An R Package for Factor Model Asset Pricing

CRAN Package

Functions for evaluating and testing asset pricing models, including estimation and testing of factor risk premia, selection of "strong" risk factors (factors having nonzero population correlation with test asset returns), heteroskedasticity and autocorrelation robust covariance matrix estimation and testing for model misspecification and identification. The functions for estimating and testing factor risk premia implement the Fama-MachBeth (1973) doi:10.1086/260061 two-pass approach, the misspecification-robust approaches of Kan-Robotti-Shanken (2013) doi:10.1111/jofi.12035, and the approaches based on tradable factor risk premia of Quaini-Trojani-Yuan (2023) doi:10.2139/ssrn.4574683. The functions for selecting the "strong" risk factors are based on the Oracle estimator of Quaini-Trojani-Yuan (2023) doi:10.2139/ssrn.4574683 and the factor screening procedure of Gospodinov-Kan-Robotti (2014) doi:10.2139/ssrn.2579821. The functions for evaluating model misspecification implement the HJ model misspecification distance of Kan-Robotti (2008) doi:10.1016/j.jempfin.2008.03.003, which is a modification of the prominent Hansen-Jagannathan (1997) doi:10.1111/j.1540-6261.1997.tb04813.x distance. The functions for testing model identification specialize the Kleibergen-Paap (2006) doi:10.1016/j.jeconom.2005.02.011 and the Chen-Fang (2019) doi:10.1111/j.1540-6261.1997.tb04813.x rank test to the regression coefficient matrix of test asset returns on risk factors. Finally, the function for heteroskedasticity and autocorrelation robust covariance estimation implements the Newey-West (1994) doi:10.2307/2297912 covariance estimator.

  • Version2.1.0
  • R version≥ 4.3.0
  • LicenseGPL (≥ 3)
  • Needs compilation?Yes
  • Last release04/15/2024

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  • Imports2 packages
  • Suggests1 package
  • Linking To2 packages