From ETF.com:
Building upon the work of Harry Markowitz, the trio of John Lintner, William Sharpe and Jack Treynor are generally given most of the credit for introducing the first formal asset pricing model, the capital asset pricing model (CAPM). It was developed in the early 1960s....MORE
The CAPM provided the first precise definition of risk and how it drives expected returns. Another benefit of the CAPM, and of later asset-pricing models as well, is that it allowed us to understand if an active manager who outperforms the market has generated alpha, or whether that outperformance could be explained by exposure to some factor.
The CAPM looks at risk and return through a “one-factor” lens—the risk and the return of a portfolio are determined only by its exposure to market beta. This beta is the measure of the equity-type risk of a stock, mutual fund or portfolio relative to the risk of the overall market.
The CAPM was the financial world’s operating model for about 30 years.
However, like all models, it was by definition flawed or wrong. If such models were perfectly correct, they would be laws, like we have in physics. Over time, anomalies that contradicted the CAPM began to surface. The model, researchers found, was only able to explain about two-thirds of the differences in returns between diversified portfolios.
Among the biggest problems for the model were issues related to size and value. Academics were publishing papers showing that small-cap and value stocks were outperforming, even after accounting for their higher betas.
Fama-French And Beyond
For example, in a 1992 paper, Eugene Fama and Ken French proposed that, along with the market factor of beta, exposure to the factors of size and value explain the cross section of expected stock returns. The Fama-French model greatly improved upon the explanatory power of the CAPM, accounting for more than 90 percent of the differences in returns between diversified portfolios. However, there were still some significant anomalies, with momentum being perhaps the most important.
In 1997, Mark Carhart—in his study, “On Persistence in Mutual Fund Performance”—was the first to use momentum, together with the Fama-French factors, to explain mutual fund returns. The addition of momentum to the model further improved its explanatory power.
As a result, the new four-factor model—beta, size, value and momentum—became the standard tool used to analyze and explain the performance of investment managers and investment strategies.
However, there still remained a number of anomalies that the four-factor model could not adequately explain.
The Latest Research
Kewei Hou, Chen Xue and Lu Zhang—the authors of the 2012 study, “Digesting Anomalies: An Investment Approach”—proposed yet another four-factor model, one that went a long way toward explaining many of the anomalies that neither the Fama-French three-factor, nor the Carhart four-factor, models could.
The authors updated their study in October 2014, and the paper was accepted for publication in the Review of Financial Studies. The study now covers the period from 1972 through 2012.
The authors called their model the q-factor model. Its four factors are:
- The market excess return (beta).
- The difference between the return on a portfolio of small-cap stocks and the return on a portfolio of large-cap stocks. The size factor earned an average return of 0.31 percent per month with a t-stat of 2.12.
- The difference between the return on a portfolio of low-investment stocks and the return on a portfolio of high-investment stocks. The authors write: “Intuitively, investment predicts returns because given expected cash flows, high costs of capital imply low net present values of new capital and low investment, and low costs of capital imply high present values of new capital and high investment.” They noted that the investment factor is highly correlated (0.69) with the value premium, suggesting that it plays a similar role to that of the value factor. The investment factor earned an average return of 0.45 percent per month with a t-stat of 4.95.
- The difference between the return on a portfolio of high return-on-equity (ROE) stocks and the return on a portfolio of low return-on-equity stocks. They write: “ROE predicts returns because high expected ROE relative to low investment must imply high discount rates. The high discount rates are necessary to offset the high expected ROE to induce low net present values of new capital and low investment.” The profitability factor earned an average return of 0.58 percent per month with a t-stat of 4.81. The authors noted that the profitability factor has a high correlation (0.50) with the momentum factor, and it plays a similar role as the momentum factor in analyzing performance....
HT: Abnormal Return
See also:
Improving on the Four-factor (beta, size, value, momentum) Asset Pricing Model
"A new benchmark model for estimating expected stock returns"
Fama-French Have A Come-to-Buffett Moment
Rob Arnott's Research Affiliates: "Finding Smart Beta in the Factor Zoo"
"Two centuries of trend following"
"The Equation that Will Change Finance"
and many more. Use the 'search blog' box if interested.
