empfin - Empirical Finance Tools in Python

empfin is a Python toolkit for empirical asset pricing models and risk premia estimation. This library is in active development and aims to implement models from all corners of the literature.

What's Inside

Currently available models for estimation of risk premia:

• TimeseriesReg: single-pass OLS time-series regression, described in Cochrane (2005), Section 12.1
• CrossSectionReg: two-pass cross-sectional regression, described in Cochrane (2005), Section 12.2
• NonTradableFactors: iterative maximum-likelihood estimator for non-tradable factors, described in Campbell, Lo & MacKinlay (2012), Section 6.2.3
• RiskPremiaTermStructure: term structure of risk premia with a single factor, tradable or not, following Bryzgalova, Huang & Julliard (2024). I would like to thank the authors for sharing their replication files.

Examples

For each model, there is a jupyter notebook with examples of their use.

Installation

pip install empfin

References

Bryzgalova, Huang, and Julliard (2024) “Macro Strikes Back: Term Structure of Risk Premia” Working Paper

Cochrane (2005) "Asset Pricing: Revised Edition". Princeton University Press.

Campbell, Lo, and MacKinlay (2012) "The Econometrics of Financial Markets"

Library Citation

Gustavo Amarante (2026). empfin - Empirical Finance Tools in Python. Retrieved from https://github.com/gusamarante/empfin