This brief is the first in a series discussing performance metrics that are important to mutual fund investors. Absolute performance is vital, but does it tell the whole story? If it did, nobody would ever invest in the trillions of dollars of U.S. Government securities which currently yield only a few basis points. While this is an extreme example, it does highlight the central principle of the Capital Asset Pricing Model (CAPM), which says that there are two factors driving compensation to investors: The time value of money, and risk. While the time value of money is generally represented by the "risk-free rate" (the yield on said government securities), risk is more open to interpretation. One commonly accepted method of understanding the risk of an investment is by calculating its beta.

Beta (β) may be the second letter of the Greek alphabet, but it's a good first step in assessing risk. And while beta is commonly calculated for individual stocks, it is equally suited for use in the analysis of a portfolio, such as a mutual fund portfolio. The beta of a portfolio of stocks represents the weighted sum of the individual stock betas in that portfolio.

 

Beta, simply put, tells you how sensitive an investment is to moves in the overall market. In most applications, "the market" is represented by choosing a proxy, such as the S&P 500 (or some other relevant index) and a time period. By definition, the market will have a beta of 1.0. An investment that tends to be more volatile than the market will have a beta greater than 1.0; less volatile, less than 1.0. Beta can be negative in the case of an investment that tends to move in the opposite direction of the market, or zero when they are totally uncorrelated. As an example, suppose an investment portfolio has a beta of 1.2. If the portfolio's relevant index were to go up 10% according to CAPM, the investment portfolio could be expected to go up by 10% x 1.2, or 12%.

 

It should be noted though, that beta does not necessarily tell how volatile a fund is in absolute terms, but rather how it historically has reacted to changes in the market as a whole. Other measures of risk such as standard deviation, or the dispersion of returns around their mean, are also informative. But knowing beta is one aspect of knowing how and why your fund will perform under various market conditions. 

When CAPM was developed in the 1960s by Jack Traynor, William Sharpe, John Lintner and Jan Mossin, the researchers posited that higher beta stocks yielded higher expected returns and indeed this has been a commonly accepted theorem. But in September 2013, Malcolm Baker, Brendan Bradley and Ryan Taliaferro published   The Low Beta Anomaly: A Decomposition into Micro and Macro Effects. The authors found strong empirical evidence that low beta stocks have tended to outperform higher beta stocks, and the results are durable and more pronounced when industry and geography effects are removed. The outperformance, they theorize, is a result of market inefficiencies caused by lower demand for low-beta stocks and higher demand for high-beta stocks. In an effort to exceed benchmarks, institutional investors often find low risk stocks unattractive.