How to Explain the Cross-Section of Equity Returns through Common Principal Components

In this paper, we propose a procedure to obtain and test multifactor models based on statistical financial factors. A major issue in the factor literature is select factors included model, as well construction of portfolios. We deal with matter using dimensionality reduction technique designed work several groups data called Common Principal Components. block-bootstrap methodology developed assess validity model significance parameters involved. Data come from Reuters, correspond nearly 1250 EU companies, span October 2009 2019. also compare our bootstrap-based inferential results those obtained via classical testing proposals. Methods under assessment are time-series regression cross-sectional regression. The main findings indicate that proposed improves Capital Asset Pricing Model regard adjusted-R2 regressions. Cross-section reveal Market related Momentum mean stocks’ returns have positive risk premia for analyzed period. Finally, observe tests statistics more conservative null than procedures.