Download the Factor Library Grid from Hugging Face

Returns the tidy-finance/factor-library-grid dataset, which describes every portfolio construction available in the factor library (one row per construction, identified by id). Use the returned tibble to discover which (sorting_variable, weighting_scheme, rebalancing, ...) combinations exist before requesting their returns with download_factor_library_ids().

Usage

download_factor_library_grid(refresh = FALSE, grid_revision = "main")

Arguments

refresh

Logical(1). If TRUE, the grid is downloaded again and replaces the copy cached in the current session. Defaults to FALSE.

grid_revision

Character(1). The revision of tidy-finance/factor-library-grid to read: a commit hash, a branch, or a tag. Defaults to "main", the latest release. Pin it to the release of the returns, see the section Revisions of download_data_huggingface().

Value

A tibble with one row per portfolio construction in the factor library, including the integer id column used by download_factor_library_ids().

Details

Equivalent to calling download_data("Tidy Finance", "factor_library_grid").

The grid is downloaded once per R session and revision and cached in memory, so repeated calls (including those made by download_factor_library_ids() and download_data("Tidy Finance", "factor_library", ...)) reuse it. Set refresh = TRUE to download it again. Each revision is cached separately and takes about 450 MB of memory.

See also

Other download functions: download_data(), download_data_constituents(), download_data_damodaran(), download_data_factors_ff(), download_data_factors_q(), download_data_fred(), download_data_fred_md(), download_data_huggingface(), download_data_jkp(), download_data_macro_predictors(), download_data_osap(), download_data_pastor_stambaugh(), download_data_risk_free(), download_data_stambaugh_yuan(), download_data_stock_prices(), download_factor_library_ids()

Examples

if (FALSE) { # \dontrun{
  download_factor_library_grid()
  download_factor_library_grid(
    grid_revision = "a5a74cdf1df0c2c3d1ce3d7bf6403a8386fbf99d"
  )
} # }