The Beta Game – Under the Hood: What’s In Your Index? [Part II] by Horizon Kinetics

In Part I of The Beta Game, we described how this one measure of “risk”– in quotes, because the only thing that beta measures is how much a stock price varied relative to the S&P 500 in the past 1, 3 or more years –which is on every ETF factsheet, has become such a built-in part of the security and ETF selection process, that one can’t even locate a high-beta ETF with any meaningful amount of assets. This is no exaggeration: we found 3 ETFs labeled high beta, and they have a grand total of $82 million of AUM. That is 0.4% of the amount of assets in 10 ETFs labeled low volatility, with a total of $22 billion of AUM, and that’s not a complete list. Essentially, in the post-2008/2009 envi-ronment, any portfolio with a high beta is unmarketable.

One of the questions from Part I was how can a volatile security have a low beta? The iShares Nasdaq Biotechnology ETF had a much lower beta than the S&P 500 (until just the last few months). The iShares MSCI Frontier 100 ETF (with 26% in Kuwait, 15% in Nigeria, and 10% in Pakistan) is down nearly 20% for the year (as of mid-December, 2015) but has a beta of 0.64 – that means, at least in Wall Street statistics, it’s one third less risky than owning the S&P 500. Want to exchange your U.S. stocks for those? One problem is that when one calculates a beta, one is also supposed to calculate the coefficient of determination. That number is a measure of the reliability of the beta. The field of statistics includes an enormous amount of work designed to test and describe the degree to which any given result is reliable or valid. Election poll results are presented alongside a measure of accuracy, like plus or minus 5%. Yet, one is unlikely to find a factsheet of any index anywhere in the world on which the coefficient of determination appears alongside the beta with an explanation of what it is and how one utilizes it. In fact, we will give honorable mention to anyone who finds one. Academic literature is filled with studies about how unreliable beta is, but it sure helps sell a lot of product.

Beta Game

For instance, we constructed (at least, that is our claim) the world’s lowest-beta long-only equity/commodity index. It had, when calcu-lated as of August 31st, only 46% of the risk of the S&P 500, a beta of 0.456. (The fig-ure as of November 30th would be 0.603.) Here it is: you can own a portfolio of emerging markets (60%), frontier markets (10%), an additional dollop of India (10%), and silver (20%). Are you in? Send us your U.S. equity portfolios, and we’ll sell those securities in an orderly fashion in exchange for this lower-risk portfolio. How much do you believe in the beta?

The essential limitation and, paradoxically, risk of using beta as a measure of risk is that it is nothing much more complicated than adding up the daily historical results of a stock or a fund versus the S&P 500 or some other bench-mark. There’s nothing predictive about it; it doesn’t suggest if that relationship will change. The iShares China Large-Cap ETF has a beta less than 1. But could not China’s actions in the South China Sea, particularly around the Spratly Islands, have some unfortunate consequences that impact their stock market; or the cessation of their massive effort to artificially support stock prices? As for Kuwait, given the neighborhood it occupies, merely because it has not yet experienced significant volatility is not to say that this cannot happen.

It is worthwhile remembering that the Shanghai Stock Exchange was first established in 1866. All of its shares became worthless in 1949 when the Communists assumed control over what was once called Mainland China. Similarly, a Warsaw Stock Exchange existed as early as the 15th century in Poland. It stopped existing in 1939. There were also exchanges in Krakow, Katowice, Lvov, Lodz, Poznan, and Wilno, and all disappeared. There was a Bucharest Stock Exchange in Romania as early as 1839. It disappeared in 1949, with the Communist takeover.

A student of historical statistics in 1948 might have been tempted to conclude that the Bucharest exchange was uncorrelated with the Shanghai exchange. This proved not to be the case, as both exchanges became worthless almost at the same time. Surely there must be a better way to measure risk than historical statistics.

Another question from Part I was why an investor would even have an interest in a high-beta security? An awful lot of college graduates today – and non-graduates and high school students – dream of creating a new phone app that will strike a chord within the vast smart phone user base: a guitar tuner application, an app to locate a lost phone, or to remotely program your television. No one tells them it’s a foolish idea – programmers like that are a new form of rock star. What would be the corollary in the investment world? How about a strategy that selects the stocks in an industry that has had the greatest declines, but only companies that have strong balance sheets and positive cash flow, so that the selection is about low valuation, not low business or balance sheet quality? Like in the oil industry? Like blue chip companies such as Chevron or Schlumberger, still enormously profitable after a precipitous drop in their revenues, and which have weathered such environments many times before, and which would produce 50% returns just to recover to their previous levels? It’s not our cup of tea, but it’s not a bad idea. And it would be a portfolio diversifier. Can’t happen. Really, it can’t. Why? Because that index won’t back test well. Which is to say that the standardized historical statistic, beta, will produce an unacceptable figure. The energy companies dropped more sharply in price than the S&P 500, which means they all have a beta greater than 1.0. The ETF manufacturer won’t even bother to try to make the ETF. How do we know? Because it was tried.

In the earlier years of the indexation era, there were a number of attempts to create ETFs based upon contrarian investment approaches. A contrarian is one who invests by purchasing assets that have performed poorly; in other words, one who invests in a manner adverse to the prevailing sentiment of the moment. Some of the most successful and famous investors of all time have been contrarians. Such a list would include John Templeton and Sam Zell, as well as Carl Icahn. The list of contrarians could well be much longer, if such a list were ever to be compiled.

Unfortunately—or perhaps fortunately, depending on one’s perspective—such investment strategies are rarely em-ulated in the world of indexation. The market long ago pronounced judgment upon the contrarian approach, and it has been found to be wanting. A Russell Contrarian ETF (CNTR), was launched in 2011; it closed in 2012 due to lack of interest. A similarly

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