It’s been almost 17 years since two economists at the University of Chicago, Eugene Fama and Kenneth French, published an attack on the stock price measure of risk known as “beta,” prompting “Beta is Dead” headlines from numerous financial publications. While these obituaries may have been a bit premature (beta is still widely taught in university finance courses and widely accepted in the business valuation field), the groundbreaking article caused some irreparable damage to beta’s reputation. Now, with the recent surge in popularity of ETFs, beta has been reinvented as a metric for evaluating and comparing the efficiency of funds.
A Quick Refresher
For those far removed from their Finance 101 days, beta is a component of the Capital Asset Pricing Model (CAPM for short), one of the most influential theories in financial economics. Beta reflects the relative volatility of a stock – how much the price of an individual security moves up or down compared to how much the market as a whole moves. If a stock increases (or decreases) exactly in line with the market, its beta is 1. If a stock increases by 10% when the market increases by 5%, its beta is 2. Classical theory held that the more volatile the stock (i.e., the higher its beta), the riskier it is. The tenet of CAPM states that the only reason investors should earn more by investing in one stock over another is the relative riskiness of the securities.
The “Death” of Beta
When Fama and French examined stock returns on the NYSE, AMEX, and NASDAQ between 1963 and 1990, they found that beta did not explain the difference in stock performance. They did, however, find that a company’s total market value and its price-to-book value ratio explained differences in returns. The conclusion reached by many following the publication of their paper: CAPM is wrong.
Since the publication of the paper, debate has raged back and forth, with several compelling counters to Fama and French’s original publication coming to light. As I mentioned previously, beta has not been abandoned, and is in fact still widely taught in many university finance courses.
With the advent of ETFs, beta has developed a new significance. As opposed to actively-managed mutual funds, ETFs do not seek to beat the market. Rather, their goal is to move in line with a selected market index (e.g., IVV seeks to replicate the return of the S&P 500). In other words, many ETFs strive for a beta of 1 relative to the underlying market index. The closer an ETF’s beta is to 1 relative to its benchmark, the more efficiently the ETF is tracking its benchmark index.
The following table presents the five-year weekly betas of several iShares ETFs:
The betas of each of these funds relative to their resepctive benchmarks is very close to 1, indicating that these funds do an excellent job of tracking their target index. Similarly, if we calculate the betas of some leveraged ETFs, we can analyze how closely these funds meet their target amplification percentage.
For these 2.5x leveraged bull and bear funds, the closer the beta is to 2.5 (or -2.5), the closer the fund comes to replicating the intended return. So we can be confident that these Direxion 2.5x leveraged funds have historically performed as expected. A beta that varies significantly from the stated target return percentage should raise an immediate red flag for any investor.
So What’s it Good For?
I’m not making any argument regarding the merits of beta as a predictor of stock returns. I haven’t developed a groundbreaking economic corollary centered around beta. I’m simply noting that beta is a meaningful metric as it relates to evaluation of ETF performance. When seeking an efficient way to gain exposure to a broad index, beta can be used as an analytical tool to grade ETFs on their ability to meet their stated goal.
Disclosure: At the date of publishing, the author currently owns shares of an ETF mentioned in this article: IVV.