Package: intrinsicFRP
Title: An R Package for Factor Model Asset Pricing
Version: 2.1.0
Date: 2024-04-15
Maintainer: Alberto Quaini <alberto91quaini@gmail.com>
Authors@R: 
    person(given = "Alberto", family = "Quaini", 
           email = "alberto91quaini@gmail.com", 
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-1251-0599"))
Description: 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 Bryzgalova-Quaini-Trojani-Yuan
        (2025) <doi:10.2139/ssrn.4574683>. The functions for selecting
        the "strong" risk factors are based on the Oracle estimator of
        Bryzgalova-Quaini-Trojani-Yuan (2025)
        <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.
License: GPL (>= 3)
URL: https://github.com/a91quaini/intrinsicFRP
BugReports: https://github.com/a91quaini/intrinsicFRP/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
LinkingTo: Rcpp, RcppArmadillo
Imports: glmnet, graphics, Rcpp
Depends: R (>= 4.3.0)
LazyData: true
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Repository: https://a91quaini.r-universe.dev
Date/Publication: 2026-04-03 17:11:27 UTC
RemoteUrl: https://github.com/a91quaini/intrinsicfrp
RemoteRef: HEAD
RemoteSha: 164e809f15c7667b2e1d4aeef93cd2ede3a5082b
NeedsCompilation: yes
Packaged: 2026-07-02 07:50:26 UTC; root
Author: Alberto Quaini [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-1251-0599>)