Empirical Finance Tools
Project description
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 implment 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 12.1CrossSectionReg: two-pass cross-sectional regression, described in Cochrane (2005), Section 12.2NonTradableFactors: iterative maximum-likelihood estimator for non-tradable factors, described in Campbell, Lo & MacKinlay (2012), Section 6.2.3RiskPremiaTermStructure: term structure of risk premia with a single factor, tradeable 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 and Market Segmentation” Working Paper
Cochrane (2009) "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
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