Application of BART to Fama&French asset pricing model

Bayesian additive regression tree (BART) models are becoming increasingly popular in literature thank to their high precision and adaptability to many different data settings. From the basic model, many improvements have been proposed, such as BART models that adapt to sparsity in the data and smoothness in the underlying true function. Others have attempted to provide models that intercept causation effects and others to provide some background theory. In this thesis I propose an application to economics, through BART estimation of the five factor asset pricing model by Fama & French. The aim is to give evidence in favor or against the correct specification of the model.