Projects

bayesfm

Python package to run Bayesian Fama-MacBeth Regressions from Bryzgalova, Huang & Julliard (2024). As presented by the authors, this methodology provides reliable risk premia estimates for both tradable and nontradable factors, detects those weakly identified, delivers valid credible intervals for all objects of interest, and is intuitive, fast and simple to implement. You can view bayesfm on PyPi or GitHub

DSGEpy

This is a Python library to specify, calibrate, solve, simulate, estimate and analyze linearized DSGE models. The specification interface is inpired by dynare, which allows for symbolic declarations of parameters, variables and equations. This library is an effort to bring the DSGE toolset into the open-source world in a full python implementation.

You can find more details about on dsgepy.com

pyAA

This repository was born as a quantitative finance project during my studies for the CQF, but it ended up as an all-around finance project. You can find it here.

pyacm

Implementation of “Pricing the Term Structure with Linear Regressions” from Adrian, Crump and Moench (2013). This library prices the time series and cross-section of the term structure of interest rates using a three-step linear regression approach. Computations are fast, even with a large number of pricing factors. Generates estimates for term premium, risk neutral yields and expected returns. You can view pyacm on PyPi or GitHub