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domain = "pseudo" to download_data()
for generating pseudo data with the same schema as the corresponding
real domain. Supported datasets in this release:
"crsp_monthly", "crsp_daily",
"compustat_annual", "compustat_quarterly", and
"ccm_links" (all mirroring domain = "wrds").
Internally, every domain = "pseudo" call funnels through
simulate_pseudo_data(), the unexported router that
dispatches to per-dataset generators. Per-dataset entry points
(download_data_pseudo_crsp(),
download_data_pseudo_compustat(),
download_data_pseudo_ccm_links()) remain exported for
direct use. All generators accept n_assets and
seed arguments; identical (seed, n_assets)
yields the same identifier universe across datasets, so pseudo CRSP and
Compustat join cleanly via add_ccm_links = TRUE or
ccm_links. Daily CRSP is generated on weekdays only.download_factor_library_grid() to fetch the
tidy-finance/factor-library-grid dataset from Hugging Face.
Also accessible via
download_data("tidyfinance", "factor_library_grid").test-coverage.yaml workflow and badge to
README.set_wrds_credentials()).httr2, so frenchdata is no longer declared in
Imports. The behavior of
download_data_factors_ff() is unchanged.download_data("tidyfinance", "factor_library", ...) now
honors the canonical start_date and end_date
arguments, filtering the returned portfolio returns to the requested
range. When both are omitted, the full history is returned and the
standard “Returning the full data set” message is emitted (via
validate_dates()). Previously these arguments were accepted
but silently ignored for the factor library.using-tidyfinance and
dates-in-tidyfinance vignettes. Both predated the current
download_data() interface and are superseded by the package
manuscript. knitr and rmarkdown are no longer
declared in Suggests, and VignetteBuilder has
been dropped from DESCRIPTION.download_data("tidyfinance", "factor_library", ids = <vector>)
now delegates directly to download_factor_library_ids(),
bypassing the grid filter. Passing ids together with filter
arguments raises an informative error.list_supported_types() to
list_supported_datasets() (#242).
The old name remains exported as a soft-deprecated alias that forwards
to the new function. Internal helpers were renamed accordingly
(e.g. list_supported_types_ff() ->
list_supported_datasets_ff()).download_data_constituents() now drops symbols equal to
"-".only_us parameter in
download_data_wrds_compustat() to only_usd to
reflect that the filter keeps USD-denominated shares only. The old name
is deprecated and forwards to only_usd with a warning.arrow, glue, and
stringr dependencies and added
nanoparquet.implement_portfolio_sort() as a convenience
wrapper that combines sample construction filtering and portfolio return
computation into a single call.download_data_risk_free() to download and process
risk-free rate data from FRED, splicing TB3MS (pre-2001) with DTB4WK
(from 2001 onwards) for monthly data, and using DTB3 for daily data.
Also accessible via
download_data("tidyfinance", "risk_free").download_data_wrds_crsp() to use
download_data_risk_free() (FRED-based) instead of the
Kenneth French risk-free rate when computing excess returns.download_data_risk_free().only_us parameter to
download_data_wrds_compustat().add_ccm_links, adjust_volume) to
download_data_wrds_crsp().prc_adj to "crsp_monthly" version
"v1".adjust_volume parameter for
"crsp_daily" version "v1" and
"v2" to download_data_wrds_compustat().compute_rolling_value().output parameter to estimate_model()
to also return t-stats or residuals.join_lagged_values().list_supported_indexes().download_data_huggingface() and
get_available_huggingface_files(). and support for
type = "hf_high_frequency_sp500".type parameter in favor of
domain and dataset.detail parameter to
estimate_fama_macbeth() to include average
n_obs, r_squared, and
adj_r_squared.download_data_wrds_crsp().add_lag_columns() in favor of
add_lagged_columns()."tidyfinance" with datasets
"high_frequency_sp500", "factor_library", and
"risk_free".renv due to lack of benefits.furrr).download_data_wrds_trace_enhanced() #133.list_supported_types_ff() with
underscores #134.compute_portfolio_returns() and
implement_portfolio_sort() now apply
min_portfolio_size to the reported portfolio cross-section.
For bivariate sorts this is the firm count per
(main_portfolio, date) summed across secondary buckets, not
per (main, secondary, date) cell as before. Previously,
setting min_portfolio_size to the number of cells
(e.g. n_main * n_secondary) silently voided every cell.
Univariate behaviour is unchanged. The default has changed from
0L to 1L, so each reported portfolio is
required to have at least one observation by default; pass
min_portfolio_size = 0L to deactivate the check. The param
documentation has also been corrected to reflect that small portfolios
receive NA (not zero).compute_long_short_returns() no longer errors with
object 'top' not found when the input panel contains only
one distinct portfolio (e.g., because assign_portfolio()
collapsed to a single bucket on a constant sorting variable). The
long-short return is now NA on such dates, consistent with
“no investment, no return”, instead of crashing.download_stock_prices()because they were blocked.download_constituents() and
download_stock_prices() now also fail gracefully with
informative messages instead of errors or warnings.download_factors() returns empty data frame with
date column to ensure vignettes are built even if resources
are unavailable.start_date and end_date validation
across applications.download_*() functions to cover
unavailable or broken resources.add_lag_columns() function that is
more efficient than lag_column()download_macro_predictors(),
download_factors(), and download_osap() now
fail gracefully with informative messages instead of errors or
warnings.ccmxpf_linktable to the new WRDS default
ccmxpf_lnkhist.download_factors_q()winsorize() by reducing quantile
recalculationsdownload_data_wrds().estimate_model(),
estimate_betas(), and
estimate_fama_macbeth().download_data_wrds_clean_trace() to
download_data_wrds_trace_enhanced() for improved
consistency.vcov_options parameter to
estimate_fama_macbeth().list_supported_indexes() and
download_data_constituents() to download index
constituents.estimate_betas() to estimate risk factor
betas.estimate_fama_macbeth() to estimate Fama-MacBeth
models.download_data_constituents() to download index
constituents.download_data_osap() to download data from Open
Source Asset Pricing.download_data_fred() to download data from
Federal Reserve Economic Data.compute_portfolio_returns() to implement
different portfolio sorting approaches.compute_long_short_returns() to quickly compute
long-short portfolio returns.compute_breakpoints() to make
assign_portfolio() more flexible.breakpoint_options() and
data_options() to provide more flexibility with respect to
column names.mktcap_lag in
monthly CRSP.cli for error messages and warnings.NULL for optional default values.readxl dependency from
download_data_macro_predictors().check_if_package_installed()
function.estimate_model() to support both
estimate_betas() and
estimate_fama_macbeth().assign_portfolio() to support
compute_portfolio_returns().download_data_stocks() to
download_data_stock_prices() for better naming.list_supported_types()). All type names are created from a
string cleaning algorithm and are hence more consistent. We kept
implicit support for legacy type names to avoid breaking existing
code.download_data_stocks().wrds_compustat_quarterly.additional_columns option
for CRSP and Compustat instead of having the error prone option to pass
columns via ....-999 by NA in Fama-French types,
which was missing in the initial implementation.download_data_factors() to support all available column
names in the Fama-French universe.start_date and end_date optional
with a message to user which dates are used as defaults.date column and its references across WRDS
types (see corresponding vignette for more information).tidyfinance-package.R
file.tidyverse style.domain and as_vector parameters to
list_supported_types()... with additional_columns
parameter and ensured that CRSP and Compustat types consider it
correctlymkt_excess column from type
“wrds_crsp_monthly”fixed = TRUE to grepl() calls with
fixed stringsNA_real_ instead of
as.double(NA)toString() instead of paste0()
with collapsedplyr::between() instead of unequal
signsvignettes/using-tidyfinanceset_wrds_credentials() function for a guided tour
to store login data"factors_ff_industry_*" data
typeshml and smb columns from
"wrds_crsp_monthly" output"v2" of
"wrds_crsp_*" data typesdownload_data* functions into multiple
files for better maintenanceThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.