Multi-factor asset pricing models. An application to the pricing of equity indexes

This thesis investigates how well multi-factor asset pricing models explain the daily returns of U.S. equity indexes, specifically the Russell 3000, the Russell 2000, the Russell 500 and the Russell Top 50, over the period from December 2013 to November 2024. By comparing the Capital Asset Pricing Model, the Fama and French three-factor model and the Fama and French five-factor model, the study highlights that size consistently emerges as the most significant determinant of cross-index return differences, with the Russell 2000 (small-cap) showing the greatest sensitivity to the size factor. Although adding Fama and French factors (value, profitability and investment factors) mildly enhances explanatory power, all indexes exhibit negative alphas, indicating that certain systematic risks or market phases are not fully captured by these models. Overall, the results underscore that in our dataset newer multi-factor approaches refine performance attribution but leave a notable portion of short-term volatility unexplained.