Fama–French Three-Factor Stock Selection and Alpha Ranking

Summary

The document introduces factor-based stock selection and groups factors into company fundamentals, external conditions, and market behavior. It surveys classic models, including Fama–French, Carhart, and other factor sets, and explains that there is no settled answer to how many factors a useful model should contain.

Its main methodological section describes the Fama–French three-factor construction. Stocks are sorted by market capitalization and book-to-market ratio; small-stock portfolios relative to large-stock portfolios form SMB, while high book-to-market portfolios relative to low ones form HML. The proposed selection idea estimates each stock’s alpha against the model and buys ten stocks with the lowest negative alpha. The article characterizes negative alpha as undervaluation, but that interpretation is asserted rather than empirically demonstrated. It provides no performance results, implementation details, or discussion of estimation error, transaction costs, short positions, or out-of-sample validation, so the strategy should be treated as a conceptual outline.

Key ideas

• Factor models select stocks using characteristics that may relate to future returns.
• Factors can describe company fundamentals, external conditions, or market behavior.
• The Fama–French model adds size and value factors to the market factor.
• SMB compares small-cap portfolios with large-cap portfolios, while HML compares high book-to-market portfolios with low ones.
• The proposed strategy buys stocks with the lowest negative model alpha, though the document offers no empirical validation.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.