Beyond Fama-French: additional factors driving returns on the Moroccan stock market

Purpose This study has two key objectives: (1) to investigate stock anomalies in the Moroccan stock market and identify risk factors explaining return variations, and (2) to compare factor combinations to propose an optimal multifactor model. Design/methodology/approach Using data from all firms listed on the Casablanca Stock Exchange (2001–2020), we employ Fama and MacBeth (1973) methodology to investigate stock anomalies related to fundamental firm characteristics and the momentum anomaly. We test single-factor and multi-factor models. Subsequently, we conduct factor spanning tests and compare models using multiple approaches to identify the most parsimonious and statistically robust specification. Findings The Fama and MacBeth (1973) regressions reveal disparities in factor explanatory power. Market capitalization and price-to-cash flow ratio exhibit the weakest effects, while book-to-market and debt-to-equity ratios show moderate influence. The price-to-earnings and price-to-sales ratios demonstrate stronger explanatory power, with momentum emerging as the most robust factor. A parsimonious three-factor model, comprising the market factor, price-to-sales, and momentum, outperforms competing models, including Fama and French model (2018). Originality/value Given Morocco's prominent position as a leading financial hub in Africa, the study underscores the relevance and growing interest in its stock market. It contributes to limited asset pricing literature on Morocco by proposing a superior alternative to traditional multifactor models. Our findings highlight the most significant anomalies whose variables exhibit greater explanatory power than those in standard models, offering a robust framework applicable to other emerging markets where conventional models often underperform.