stock that fluctuates more than the market is considered to be more risky and has a higher beta. One that fluctuates less is less risky and has a lower beta. How did these professors know that investors measured risk strictly by the volatility of the stock? They didnt, nor did they do any research to find out, other than the original studies of the correlation between volatility and retum, with results which were mixed at best. The academics simply declared it as fact. Importantiy, this definition of risk was easy to use to build complex market models, and thats what the professors wanted to do.

Economists find this view of risk compelling, if not obsessional, because it is the way the rational man should behave according to economic theory. If investors are risk-averse in markets, and the academics can show this to be so by their definition, -then the economist has proof of a central concept-or pet crotchet-of economic theory. Voila! Man is a rational decision-maker. If investors will take greater risk only if tiiey receive higher retums-Eureka! A six lane highway opens between investment markets and microeconomic theory. By this highway, investment markets deliver to economic theory the ultimate payload: proof positive of rational behavior in markets. Right or wrong, the idea is too seductive for economists to pass up.

But the critical question is still there, why this measure of risk rather than the analysis of a companys financial strength, eamings power, outstanding debt, or dozens of other measures that Graham and Dodd or corporate management use? Sure, this one is alluring to economic types, but what else has it got going for it?

You dont have to look all that closely to see large holes in this definition begin to appear. Investors may not like volatility in down markets, but they certainly dont object to their stocks outperforming the averages on the upside. What about the psychological and financial risk that we looked at in crisis investing, or the risk of loss of capital through inflation in chapter 13? Finally, the headlong charge into aggressive stocks, which are highly volatile and retum Uttle, certainly contradicts the defirution. From the beginning, then, this definition of risk seemed unrealistic.

Whether unrealistic or not, an entire generation has been trained to believe risk is volatility. Perhaps you read the various guides on how to select mutual funds by their volatility. Possibly you accept these measures without question. Most people do. But in tmth they are faulty.

In the first place it has been known for decades that there is no corte-lation between risk, as the academics define it, and retum. Higher volatility does not give better results, nor lower volatility worse.

J. Michael Murphy in an important but little-read article in the Journal of Portfolio Management in the fall of 1977 reviewed die research on risk. Some of the conclusions were startling, at least for EMH and MPT believers. cited four studies that indicated that "realized returns tend to be higher than expected for low-risk securities, and lower than expected for high-risk securities ... or that the [risk-reward] relationship was far weaker than expected."- Murphy continued: "Other important studies have concluded that there is not necessarily any stable long-term relationship between risk and return; that tiiere often may be virtually no relationship between return achieved and risk taken; and that high volatility unit trusts were not compensated by greater returns" [italics original].

Another paper by Haugen & Heins (1975) analyzing risk concluded widi the statement: "The results of our empirical effort do not support the conventional hypothesis that risk-systematic or otherwise-generates a special reward." Remember this research was done in the mid to late seventies, just as MPT and the concept of risk-adjusted returns were starting the investment revolution, and over a decade before Nobel Prizes were awarded to its advocates.

The lack of correlation between risk and return was not the only problem troubling academic researchers. More basic was the failure of volatility measures to remain constant over time, which is central to both the efficient market hypothesis and modem portfolio theory. Although beta is the most widely used of all volatility measures, a beta that can accurately predict future volatility has eluded researchers since the beginning. The original betas constmcted by $ , Lintner, and Mossin were shown to have no predictive power, that is, die volatility in one period had little or no correlation with that in the next. A stock could pass from violent fluctuation to lamb-like docility.

Since the comerstone of MPT and an implicit assumption of EMH is that all investors are risk-averse, in the same manner, the absence of a demonstrable beta was a serious problem for the researchers from the beginning. If investors are risk-averse, beta or otiier risk-volatility measures must have predictive power. That they have not, that there is no correlation between past and future betas was a major anomaly, a "black hole" in the theory. Without a tenable theory of risk, the efficient market hypothesis was an endangered species.

Barr Rosenberg, a well-respected researcher, developed a widely used multifactor beta, which included a large number of other inputs besides volatility to measure the risk of specific securities. These multi-factor betas were often called "Barrs Bionic Betas." Unfortunately, they were as hapless as their predecessors. Other betas were experimented

with, all with the same resuh. Future betas of both individual stocks and portfolios were not predictable from their past volatility.

The evidence for the most part was kept on the back bumer until Eugene Fama put out his own paper on risk and retum in 1992. Fama had previously published a paper in 1973 (coauthored with James MacBeth) that indicated higher beta led to higher retums. It was one of the instmmental pieces in building MPT. This time collaborating with Kenneth French, also of the University of Chicago, the researchers examined 9,500 stocks from 1963 to 1990." Their conclusion was that a stocks risk, measured by beta, was not a reliable predictor of performance.

Fama and French found that stocks with low betas performed roughly as well as stocks with high betas. Fama stated that "beta as the sole variable in explaining retums on stocks ... is dead."" Write this on the tombstone: "What we are saying is that over the last 50 years, knowing the volatility of an equity doesnt tell you much about the stocks retum." Yes, make it a large stone, maybe even a mausoleum.

An article in Fortune concluded: "Beta, say the boys from Chicago, is bogus." The Chicago Tribune summed it up well: "Some of its best-known adherents have now become detractors.""

If not beta, then what? If risk cannot be measured by volatility, how should it be determined? According to French, "What investors really get paid for is holding dogs." Their study, as we saw in chapter 7, indicated that stocks with the lowest price-to-book ratios and lowest P/Es provide the highest retums over time, as do smaller capitalization companies. Stock retums are more positively related to these measurements than to beta or other similar risk criteria.*

Fama added: "One risk factor isnt going to do it." Investors must look beyond beta to a multifactor calculation of risk, which includes some value measurements and other criteria.

Buried with this canon of modem finance is modem portfolio theory, as well as a good part of EMH. Famas new findings rejected much of the academic work of the past, including his own. He said at betas graveside, "we always knew the world was more complicated." He may have known it, however he did not state it for more than two decades.

Famas statement that "beta is dead" was the shot at risk heard round the world. As one finance professor put it in discussing the Fama and French findings:

[M]odem finance today resembles a Meso-American religion, one in which the high priest not only sacrifices the followers-but even the