It provides a toolkit of econometrics commands — regression, regression diagnostics, stationarity and cointegration tests, Granger causality, GARCH volatility modelling, and panel-data estimators — that operate on any tabular dataset passed in as data.

Installation

Install from PyPI with:

pip install openbb-econometrics

Then build the Python static assets by running:

openbb-build

Quick Start

Every command is a POST endpoint that takes a data payload (a list of records, e.g. the .results of another OpenBB command) plus typed parameters, and returns an OBBject.

from openbb import obb

prices = obb.equity.price.historical(
    symbol="AAPL", start_date="2023-01-01", provider="yfinance"
).results

# Coefficient table of an OLS regression.
obb.econometrics.ols_regression(
    data=prices, y_column="close", x_columns=["open", "high", "low"]
)

# Augmented Dickey-Fuller stationarity test.
obb.econometrics.unit_root(data=prices, column="close")

# GARCH(1, 1) conditional volatility.
obb.econometrics.garch(data=prices, column="close")

To use the extension over HTTP, start the API server with openbb-api and POST to /api/v1/econometrics/<command>.

Coverage

All commands are available under obb.econometrics.*.

Tools

correlation_matrix — correlation matrix of a dataset
summary_statistics — per-column descriptive statistics

Regression

ols_regression — Ordinary Least Squares coefficient table
ols_regression_summary — OLS goodness-of-fit summary

Diagnostics

autocorrelation — Durbin-Watson autocorrelation test
residual_autocorrelation — Breusch-Godfrey residual autocorrelation test
heteroskedasticity — Breusch-Pagan and White heteroskedasticity tests
normality — Jarque-Bera normality test on residuals
variance_inflation_factor — multicollinearity (VIF) test

Time Series

unit_root — Augmented Dickey-Fuller unit root test
kpss — KPSS stationarity test
cointegration — Engle-Granger pairwise cointegration test
cointegration_johansen — Johansen multivariate cointegration test
causality — Granger causality test
garch — GARCH(p, q) conditional volatility model

Panel

panel_random_effects — one-way Random Effects model
panel_between — Between estimator
panel_pooled — Pooled OLS estimator
panel_fixed — Fixed Effects estimator
panel_first_difference — First-Difference estimator
panel_fmac — Fama-MacBeth estimator

See the full docs here