A Statistical Factor Asset Pricing Model Versus the 4-Factor Model

This research aims to compare the performance of a statistical factor asset pricing model with the Fama-French-Carhart 4-factor model. We perform a Principal Component Analysis (PCA) to extract latent risk factors using data of stocks listed on B3 from 2001 to 2015. We test the abilities of the two models to explain assets' returns both in the time-series and in the cross-section dimension. We found that the statistical factor models generates statistically significant abnormal returns in the time-series analysis while the 4-factor model does not. In the cross section dimension, neither model generates significant abnormal returns but they also are not able to generate positive risk premia. Similar results are found if we consider different sets of time and assets. Therefore, although the 4-factor model performs slightly better in the set of tests, neither of the models can be considered fully adequate to explain expected returns of assets in the Brazilian stock market.