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farr 1.1.1

• Cumulative event returns explicitly reject returns below -1 in DuckDB, including DuckDB 2.0 with ieee_floating_point_ops enabled (#34).

farr 1.1.0

• Expanded runnable examples and return-value documentation, documented the prediction method for rusboost() objects, and clarified which examples require internet access or database credentials.
• get_size_rets_monthly() now downloads over HTTPS to a temporary file, removes it even on failure, and restores VROOM_CONNECTION_SIZE after parsing instead of changing the caller’s files or environment (#33).
• rusboost() now retains a perfect learner as the sole predictive learner with weight 1 and reports an error if no usable learner is fitted (#32). Random undersampling handles singleton classes safely and validates class counts and majority sample sizes.
• Monthly cumulative-return windows now include the full ending month for nonzero offsets, including transitions from shorter to longer months.
• Daily and monthly cumulative event returns now handle complete losses (ret = -1) in stocks and benchmarks (#31). Missing-value handling is unchanged, and returns below -1 continue to raise an error.
• get_event_rets() now retains non-trading-day announcements (#30), measuring relative trading days from the next trading day while keeping the original announcement dates.
• Corrected get_got_data() to use rho_E for firm-specific error persistence (#29). Simulations with unequal rho_X and rho_E now follow the requested error process; equal-parameter results are unchanged.
• Refreshed aaer_dates through October 2026, with 3,386 rows. The data steps apply source-backed date and coverage corrections, preserve historical entries absent from the current SEC index, and remove exact duplicates (#27).
• Corrected five public-float dates in iliev_2010 using the original 10-Ks, including four fractional years. The original CSV is preserved, with an explicit correction table and filing references in data-raw (#28).
• Corrected tree weights in predict.rusboost(type = "prob") (#26), including predictions for a single observation or weak learner. Probability predictions require finite, nonnegative weights with a positive finite total.
• Corrected the by_tag_year documentation: year_total counts questions across all tags in a year, rather than questions with a specific tag.
• get_ff_ind() now caches downloaded Fama-French industry zip files by default and supports refresh_cache = TRUE.
• Added a pkgdown site with Bootstrap 5 styling, a dark-mode toggle, and a Quarto article scaffold.

farr 1.0.1

• Added duckdb_to_parquet().
• Fixed the lazy table returned by duckdb_to_parquet() by removing the dbplyr::sql() wrapper around read_parquet().
• Updated internet-dependent examples and tests so they do not run on CRAN.

farr 1.0.0

• The are now no duplicates in gvkey_ciks.
• There is a keep_max argument in get_me_breakpoints().
• Documentation fixes have been made.

farr 0.3.2

• The get_me_breakpoints() function works with current data format.

farr 0.3.1

• Updated code to reflect changes in tidyselect package.
• Updated code to reflect changes in Fama-French data.

farr 0.3.0

• Tweaked test_scores data (now two files).
• Added system_time().

farr 0.2.39

farr 0.2.38

• Tweaks for CRAN submission.

farr 0.2.36

• Added parquet-related functions: load_parquet() and pg_to_parquet().
• Added gvkey_ciks data.

farr 0.2.35

• Added cmsw_2018 data.
• Fixes to documentation.

farr 0.2.34

• Fixes to data and documentation.

farr 0.2.33

• Updated tests.

farr 0.2.32

• Removed duplicates from names data.

farr 0.2.30

• Added aus_banks data sets.

farr 0.2.29

• Added rusboost function.

farr 0.2.28

• Added Zhang (2007) data.

farr 0.2.27

• Added tests.
• Added examples.

farr 0.2.26

• Added sho_r3000_sample data set.
• Added sho_r3000_gvkeys data set.

farr 0.2.25

• Replaced df_to_pg() with copy_inline() from dbplyr package.

farr 0.2.24

• Added sho_r3000 data set.
• Renamed FHK data sets.

farr 0.2.23

• Added sho_tickers data set.

farr 0.2.22

• Added form_deciles function.

farr 0.2.21

• Added Reg SHO data sets (sho_pilot and sho_firm_years).

farr 0.2.20

• Added get_size_rets_monthly and get_me_breakpoints functions.

farr 0.2.16

• Removed read_only arguments.

farr 0.2.15

• Added random assignment option to get_test_scores.

farr 0.2.14

• Tweaked df_to_pg() to use VALUES.

farr 0.2.13

• Use dbQuoteLiteral() in df_to_pg().

farr 0.2.12

• Added get_test_scores() function.

farr 0.2.11

• Fixes to cumulative returns code.
• Added monthly returns.

farr 0.2.10

• Added two data sets related to LLZ 2018.
  • llz_2018: GVKEYs.
  • undisclosed_names: For disclosure variable.

farr 0.2.9

• Added idd_dates (data) and get_idd_periods() (function)
• Added state_hq data.

farr 0.2.8

• Reverted to earlier form of df_to_pg() function (#1).
• Added test_scores data.

farr 0.2.7

• Added comp data set.

farr 0.2.6

• Now use DBI::dbQuoteLiteral() in df_to_pg() function (#1).

farr 0.2.5

• Added get_ff_ind function.

farr 0.2.4

• Added get_got_data function.

These 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.