There’s a cycle in the finance world whereby good ideas become products, which sell well and spur demand for more good ideas. Current case in point: the cycle involving investable factors.
“Factors” is the catch-all term for the mechanisms that drive asset prices, and factors are being discovered almost as quickly as they can be packaged and sold to the waiting public.
The investment firms AQR Capital Management and Dimensional Fund Advisors are prominent factor users. The Maryland State Retirement and Pension System, a $52 billion plan that covers more than 400,000 workers and retirees, uses factor products. Many long/short equity hedge funds have incorporated factor hedging into their strategies, and the proliferation of low-cost exchange-traded funds and index mutual funds has made factor-style investing accessible to the retail market.
Fidelity, Vanguard, and BlackRock all offer online explainers of factors, and BlackRock has a head of factor-based strategies who proclaims on the company’s website that “factor investing is the way of the future.” “Institutional investors and active managers have been using factors to manage portfolios for decades,” reads BlackRock’s pitch. “Today, data and technology have democratized factor investing to give all investors access to these historically persistent drivers of return.” BlackRock’s site features an infographic that highlights 12 factors of importance, divided into two categories: macroeconomic (capturing broad risks across asset classes) and style (explaining returns in just one asset class).
And many dozens more are circulating, presumably keys to greater investment returns. Duke’s Campbell R. Harvey, Texas A&M’s Yan Liu, and University of Oklahoma’s Heqing Zhu have identified more than 300 factors in academic literature. City University of Hong Kong’s Guanhao Feng (a recent graduate of Chicago Booth’s PhD Program), Yale’s Stefano Giglio, and Booth’s Dacheng Xiu have collected and investigated over 100 of them—ranging from employee growth to maximum daily return.
But has the hunt for investable factors gone too far? Feng, Giglio, and Xiu are suggesting that it has. On one hand, factors are helpful. If an investor wants to have a truly balanced portfolio, she should do more than make sure she owns both stocks and bonds, and in theory she can use factors to make sure her investments truly represent a diverse basket of assets whose returns are driven by different things.
But are there really 300 separate characteristics associated with higher asset returns, or only a handful of things really driving stock prices? The hundreds of factors that appear in academic research are based on many possible company characteristics, which could, in theory, capture many types of risk. However, Feng, Giglio, and Xiu are skeptical that all these factors are useful. Two portfolios that look different from each other—for example, one that overweighs small companies and another that is heavy on illiquid companies—could end up giving investors exposure to the same underlying risk. That is, many of these factors may be redundant. Is the factor industry an example of a good idea that has gone too far?
Before there were 300 factors, there was just one, kind of. The original factor—or the forerunner of factor analysis—is, in a sense, the capital asset pricing model. Largely developed by Stanford’s William F. Sharpe, who was awarded the Nobel Memorial Prize in Economic Sciences in 1990, the CAPM posits that investors are paid for both the time value of their money and the risk they assume in holding an asset. The model has helped investors determine how much compensation they should demand for holding a risky asset.
The formula is not reliably predictive. It generates an expected return on assets based in part on the beta of a security, or its covariance with the market. Some research on the CAPM has suggested that low-beta stocks tend to have higher returns than predicted, while higher-beta stocks do not live up to expectations. Still, some finance professionals refer to the CAPM as “the one-factor model,” where market beta is the sole explanatory factor of expected returns.
In 1992, expanding on the CAPM, Chicago Booth’s Eugene F. Fama and Dartmouth’s Kenneth R. French published a three-factor model, identifying two more things that generate returns: size and value. They observed that small-cap companies outperformed large-cap ones over time, and companies with low price-to-book ratios outperformed companies with higher price-to-book ratios.
Investors generally accepted the Fama-French three-factor model, yet it still seemed incomplete to many adherents of Fama’s efficient-markets hypothesis. If markets are efficient and assets priced accordingly, a return is the compensation an investor receives for taking on some risk by holding an asset. Factors capture this risk, so when investors take on exposures to certain factors in their portfolios, they earn a risk premium as compensation. But some mutual-fund managers consistently outperformed or underperformed market benchmarks. Were they taking on risks beyond just three? The natural inclination of an efficient-markets believer, when confronted with an outperforming manager, is to assume that the manager is taking on and being paid for unquantified risks that are driving the asset returns. In 1997, Mark Carhart, who founded Kepos Capital, published an article that suggested momentum as a fourth factor.