Package: BayesianFactorZoo 0.0.0.3
Jiantao Huang
BayesianFactorZoo: Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models
Contains the functions to use the econometric methods in the paper Bryzgalova, Huang, and Julliard (2023) <doi:10.1111/jofi.13197>. In this package, we provide a novel Bayesian framework for analyzing linear asset pricing models: simple, robust, and applicable to high-dimensional problems. For a stand-alone model, we provide functions including BayesianFM() and BayesianSDF() to deliver reliable price of risk estimates for both tradable and nontradable factors. For competing factors and possibly nonnested models, we provide functions including continuous_ss_sdf(), continuous_ss_sdf_v2(), and dirac_ss_sdf_pvalue() to analyze high-dimensional models. If you use this package, please cite the paper. We are thankful to Yunan Ding and Jingtong Zhang for their research assistance. Any errors or omissions are the responsibility of the authors.
Authors:
BayesianFactorZoo_0.0.0.3.tar.gz
BayesianFactorZoo_0.0.0.3.tar.gz(r-4.5-noble)BayesianFactorZoo_0.0.0.3.tar.gz(r-4.4-noble)
BayesianFactorZoo_0.0.0.3.tgz(r-4.4-emscripten)BayesianFactorZoo_0.0.0.3.tgz(r-4.3-emscripten)
BayesianFactorZoo.pdf |BayesianFactorZoo.html✨
BayesianFactorZoo/json (API)
# Install 'BayesianFactorZoo' in R: |
install.packages('BayesianFactorZoo', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- BFactor_zoo_example - Simulated Example Dataset *'BFactor_zoo_example'*
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:368ebfbd8e. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-linux | OK | Nov 04 2024 |
Exports:BayesianFMBayesianSDFcontinuous_ss_sdfcontinuous_ss_sdf_v2dirac_ss_sdf_pvaluepsi_to_priorSRSDF_gmmTwo_Pass_Regression
Dependencies:bootbriocallrclicodacolorspacecrayoncubaturedescdiffobjdigestellipseevaluatefansifarverfftwtoolsfsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmatrixcalcMatrixModelsmcmcMCMCpackmcmcsemgcvmunsellmvtnormnlmenpnsepillarpkgbuildpkgconfigpkgloadplyrpraiseprocessxpsquadprogquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackrematch2reshape2rlangrprojrootsandwichscalesSparseMstringistringrsurvivaltestthattibbletimeDatetimeSeriesutf8vctrsviridisLitewaldowithrzoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Bayesian Fama-MacBeth | BayesianFM |
Bayesian estimation of Linear SDF (B-SDF) | BayesianSDF |
Simulated Example Dataset *'BFactor_zoo_example'* | BFactor_zoo_example |
SDF model selection with continuous spike-and-slab prior | continuous_ss_sdf |
SDF model selection with continuous spike-and-slab prior (tradable factors are treated as test assets) | continuous_ss_sdf_v2 |
Hypothesis testing for risk prices (Bayesian p-values) with Dirac spike-and-slab prior | dirac_ss_sdf_pvalue |
Mapping psi ('psi0') to the prior Sharpe ratio of factors ('priorSR'), and vice versa. | psi_to_priorSR |
GMM Estimates of Factors' Risk Prices under the Linear SDF Framework | SDF_gmm |
Fama MacBeth Two-Pass Regression | Two_Pass_Regression |