knitr::opts_chunk$set(collapse = TRUE, comment = "#>", fig.path = "README-") folder <- "literature_files"; dir.create(folder) download.file("https://www.dropbox.com/s/htnd7o9nnkk8ng8/references.bib?dl=1", paste(folder, "references.bib", sep = "/")) library(FFresearch) data(list = c("factors", "portfolios_univariate", "portfolios_bivariate", "portfolios_trivariate", "portfolios_industries", "variables", "breakpoints"), package = "FFresearch")
FFresearch packages Fama/French research data for convenient consumption by R users. The data is pulled directly from Kenneth French's online data library.
Install from github with devtools::install_github("bautheac/FFresearch")
.
The portfolios_univariate
dataset provides various feature time series for Fama/French portfolios formed on single variable sorts. Sorting variables include size, book-to-market, operating profitability and investment:
head(portfolios_univariate)
The portfolios_bivariate
dataset provides various feature time series for Fama/French portfolios formed on two variable sorts. Sorting variables include size, book-to-market, operating profitability and investment. Size concerns limit the data history to the last ten years; the full time series are available from the author upon request.
head(portfolios_bivariate)
The portfolios_trivariate
dataset provides various feature time series for Fama/French portfolios formed on three variable sorts. Sorting variables include size, book-to-market, operating profitability and investment:
head(portfolios_trivariate)
The portfolios_industries
dataset provides various feature time series for Fama/French industry portfolios [@fama_industry_1997]:
head(portfolios_industries)
The factors
dataset provides the return (factors) and level (risk free rate) time series for the classic Fama/French asset pricing factors as used in their three [@fama_cross_section_1992; @fama_common_1993; @fama_size_1995] and most recently five-factor [@fama_five_factor_2015; @fama_dissecting_2016; @fama_international_2017] asset pricing models extremely popular to the asset pricing enthusiasts:
head(factors)
The variables
dataset is a helper dataset that provides details, including construction methods, for the variables used to construct the portfolios and asset pricing factors above:
head(variables)
The breakpoints
dataset is a helper dataset that provides the times series for the variables breakpoints used to construct the variables that in turn allow the construction of the portfolios and asset pricing factors abovementioned:
head(breakpoints)
Although the FFresearch package is self-contained it belongs to the finRes suite of packages where it helps with asset pricing research and analysis.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.