v0.3.0

• Dependencies (removed statsmodels): The statsmodels dependency was dropped; the regression-based functions now use pyfixest instead. estimate_model and the cross-sectional / IID-variance steps of estimate_fama_macbeth call pyfixest.feols, and estimate_betas was rewritten to estimate rolling betas via closed-form OLS on cumulative cross-product sums (the design Gram matrix X'X and moment vector X'y are accumulated and rolled by cumulative-sum differencing, then solved once per window). This follows the fast beta estimation approach, generalized to multiple regressors, and returns coefficients identical to ordinary least squares while avoiding a full refit per window (#49).
• Docs (Great Docs): Added a Great Docs documentation site configured via great-docs.yml, including LLM-friendly artifacts (llms.txt, llms-full.txt). The API reference is generated from the numpydoc docstrings; build locally with great-docs build (on Windows set PYTHONUTF8=1 to avoid a cp1252 decode error during post-processing). The generated great-docs/ build directory is gitignored. (#29)
• Breaking (Python version): The minimum supported Python is now 3.11 (was 3.10), as required by the Great Docs toolchain.
• Docs (R parity): Fixed docstring discrepancies surfaced by the rendered reference, aligning the Python docs with r-tidyfinance: breakpoint_options (removed a duplicated breakpoints_exchanges entry and documented the previously undocumented breakpoints_min_size_threshold), create_summary_statistics (enumerated the reported statistics and detail quantiles), compute_portfolio_returns / implement_portfolio_sort (min_portfolio_size univariate/bivariate semantics and the "set to 0 to deactivate" behavior), estimate_betas (lookback annotated as int to match its use as an observation-count window), and winsorize (corrected the x type to np.ndarray and documented the [0, 0.5] range for cut).
• Polars support: the public API can now work with polars data frames via a global backend. Call tidyfinance.set_backend("polars") (default "pandas"; get_backend() reports the current setting). When set to "polars", the data-bearing functions (download_data, the estimate_*/compute_* family, add_lagged_columns, assign_portfolio's frame inputs, list_supported_datasets, etc.) return polars data frames, and all of them also accept polars input regardless of the active backend (converted to pandas internally). DataFrame outputs convert; Series/dict/ndarray returns (e.g. assign_portfolio) are left as-is, and date indices are preserved as columns. Internals remain pandas-based for now. Requires the optional polars dependency (pip install tidyfinance[polars]) (#42).
• Breaking (WRDS credentials): WRDS credentials are now read exclusively from environment variables (e.g. via a .env file). Support for config.yaml has been removed: set_wrds_credentials() now writes a .env file (with WRDS_USER and WRDS_PASSWORD), and get_wrds_connection() no longer accepts a config_path argument. The pyyaml dependency was dropped. Migrate any existing config.yaml credentials into a .env file or environment variables.
• Breaking (CRSP): the monthly CRSP price column returned by download_data(domain="wrds", dataset="crsp_monthly") is now named prc (was altprc), aligning with r-tidyfinance and both book editions. The value is unchanged — it is mthprc from the CRSP v2 monthly stock file; altprc was the legacy (v1) column name and was semantically stale for v2 downloads. Update any downstream code that referenced altprc (including the dependent mktcap computation).
• Fix (Fama-MacBeth Newey-West): estimate_fama_macbeth now matches R's sandwich::NeweyWest defaults, so the Python and R editions agree on Newey-West t-statistics. The previous implementation used statsmodels HAC with a fixed maxlags=6 and no prewhitening (textbook Newey-West 1987); the new numpy implementation uses VAR(1) prewhitening plus the automatic Newey & West (1994) bandwidth, Bartlett kernel, recoloring, and no finite-sample adjustment (verified against sandwich 3.1.1 to ~1e-13). vcov_options now mirrors R's interface (lag, prewhite, adjust) and defaults to None; the legacy maxlags key is accepted as a deprecated alias for lag (preserving the old no-prewhitening behavior) and emits a DeprecationWarning (#35).
• Fix (CRSP column order): download_data(domain="wrds", dataset="crsp_monthly") now orders listing_age before mktcap to match r-tidyfinance's download_data_wrds_crsp() (..., siccd, listing_age, mktcap, mktcap_lag, ...). Values are unchanged; only the column order differed (#36).
• Fix (TRACE regime cutoff): process_trace_data now uses the correct Dick-Nielsen (2014) enhanced-TRACE regime cutoff of 2012-02-06 (was the transposed 2012-06-02). Samples spanning Feb 6 – Jun 2, 2012 were previously cleaned under the wrong cancellation/correction/reversal regime, producing incorrect output; samples entirely after June 2012 were unaffected. This aligns the Python edition with r-tidyfinance's download_data_wrds_trace_enhanced() (#34).
• download_data() now uses the human-readable domain names returned by list_supported_datasets() (e.g., "Fama-French", "Global Q", "WRDS", "Tidy Finance"). The "pseudo" and "tidyfinance" domains were renamed to "Pseudo Data" and "Tidy Finance". The previous machine-readable domain names (e.g., "famafrench", "wrds", "pseudo", "tidyfinance") are soft-deprecated but still accepted.
• Breaking (package API): the dataset-specific _download_data_* helpers (e.g. _download_data_wrds, _download_data_macro_predictors, _download_data_constituents, _download_data_factors_ff, _download_data_factors_q, _download_data_osap, _download_data_risk_free, _download_data_stock_prices) are no longer re-exported from the package root. Public access continues via the dispatcher download_data(domain, dataset, ...). If you need a helper directly, import it from its defining module (e.g. from tidyfinance.data_download import _download_data_wrds).