How do you build a winning portfolio? Investment managers use techniques such as fundamental analysis, technical analysis, even social media analysis. They work hard to identify the “best” securities and to diversify by sector, capitalization and country. But under the rigors of academic research and analysis, those strategies have historically failed to live up to expectations.
The closest anyone has come thus far to catching the performance genie in a bottle has been factor analysis, which uses academic research to quantify the components of “alpha” (an asset’s outperformance compared to the market overall) and turn it into an objective, repeatable model of security selection.
Since the 1960s, the traditional asset pricing model has been CAPM (the capital asset pricing model), which uses a single variable — an asset’s beta, or correlation to the broad market — as a predictor of its expected future performance relative to some risk-free rate (cash or government bonds).
Then, in 1980, Rolf Banz, a former student of Eugene Fama, published a study finding that small-cap stocks had systematically outperformed large-cap stocks over time, research that resulted in the founding of Dimensional Fund Advisors (DFA) and the 1981 launch of its pioneering DFA 9-10 fund, which focused on small- and micro-cap stocks.
In 1992, Eugene Fama and Kenneth French, professors at the University of Chicago Booth School of Business, expanded on Banz’ work and published “The Cross Section of Expected Stock Returns,” expanding the single-factor CAPM into a three-factor model for analyzing security performance. To this day, this is perhaps the most widely cited paper in financial economics.
Factors are observable and quantifiable security-level characteristics that can explain differences in stock returns. Fama and French’s three-factor model identifies three characteristics that predict a stock’s performance:
- Beta, or overall market risk
- Size, with smaller companies throwing off higher returns than larger companies
- Value, measured as a security’s price-to-book ratio, with low-ratio stocks outperforming high-ratio stocks
In 1997, economist Mark Carhart posited a momentum factor (the tendency for a stock price to continue rising if it is going up and to continue declining if it is going down). More recently, Robert Novy-Marx (2012) and Fama/French (2015) have described additional factors, including profitability (stocks with a high operating profits tend to outperform) and investment (companies that invest aggressively in their business are more likely to outperform those that invest conservatively).
Numerous economists have demonstrated that, over the long term, returns of an equity portfolio can be explained almost entirely through a factor lens.
Columbia University finance professor Andrew Ang, author of “Asset Management: A Systematic Approach to Factor Investing,” uses an insightful analogy: Factors are to investment assets as nutrients are to food. Much as we eat foods for their underlying nutrients — meat or soybeans for protein, nuts for healthy oils, fruits and vegetables for vitamins and fiber — to the quantitative investment manager it is investment factors that really matter, not the assets themselves. Just as foods are bundles of nutrients, securities are bundles of factors.