Chasing Tail

I don’t intend to get overly academic with this blog. For one, if I did, I think I’d have even fewer readers than I already do. Furthermore, many of the traditional theories spewed by tenured professors who’ve never stepped foot on a trading floor have consistently proven useless in the face of great financial calamities. And the futility of mainstream financial academia has become only more glaring during the credit crisis.

Among the cornerstones of financial economics is the Efficient Market Hypothesis (EMH), which basically holds that prices of financial assets incorporate all known information and adjust quickly to reflect new data. As a result, the theory goes, an investor won’t be able to outperform the relevant benchmark through anything other than pure luck. In other words, if you believe in the EMH, you shouldn’t be wasting your time sifting through individual stocks or even delegating the task to supposedly brilliant (and undoubtedly expensive) funds. No, the EMH suggests that if you’re going to invest in an asset class, invest in the wider market – instead of an individual stock, choose the S&P 500; instead of a particular bond, pour your money into a broad fixed income fund.

To be fair, there’s much to be said for this advice. Insofar as it prevents investors from not diversifying and paying excessive fees for investment managers, the EMH is a good thing. Indeed, countless studies (see, for example, this one) suggest that mutual funds do not reliably beat indices, and when fees are taken into account, they often fall well short. In fact, even the (once) revered class of investment vehicles otherwise known as hedge funds probably don’t outperform their benchmarks net of fees. Admittedly, for a variety of reasons, historical hedge fund performance data can be unreliable, but the preponderance of evidence indicates that on average, hedge funds aren’t as magical as they’d lead some investors to believe. And, whether you believe academic studies or not, the abysmal performance of the class in 2008 should raise some serious questions. In case they don’t, I’ll raise one – how was it that equity long-short hedge funds finished down almost 40% last year, exceeding the loss of the S&P 500, when they were supposed to have next to no market exposure?

One of the reasons relates to a key deficiency of the EMH, which in a curious WSJ editorial, Professor Jeremy Siegel entirely overlooks. Before proceeding to bash Siegel, I will say that he’s smarter than I am, has more standing than I do, and has penned a finance book that’s actually worth reading (surely an admirable feat in a sector dominated by Rich Dad, Poor Dad) – pick up Stocks for the Long Run if you don’t have a copy. With that said, I find his defense of the EMH bewildering. Siegel’s essential point is that the massive losses banks incurred during the credit crisis don’t reflect any weakness in the EMH but rather a weakness in risk management.

Superficially, he’s right. In fact, I would go so far as to say that his reasoning is tautological – because banks lost loads of money, by definition they weren’t managing risk effectively. And, in a proximate sense, the EMH can’t be at fault since nobody at any institution I know of gives a shit about the theory. There’s a good chance that most don’t even know what it is. While knowledge of advanced financial math may be important in some trading functions, knowledge of broad theories about market efficiency generally isn’t.

Still, I think it’s worth noting that the credit crisis has dealt a major blow to the EMH because it’s underscored the degree to which risk is systematically mispriced. To put it in a less academic fashion, market participants tend to underweight the chance of really bad shit happening (e.g., house prices collapsing). Nassim Taleb has made a career off this observation. Noting that really bad shit goes down a lot more often than most models predict, Taleb points to the importance of what he calls “black swans,” extreme outliers that can burn holes in banks’ coffers. Eschewing the zoological definition, financial economists would explain this phenomenon by declaring that most of us don’t accurately estimate “tail risk,” the risk at the tail of a mathematical distribution.

In an efficient market, the estimation of outliers, or tail events, wouldn’t be biased. This is to say, over the long run, you couldn’t consistently make money by betting on or against extreme occurrences. And Siegel suggests that you can’t, implying that high yields on subprime securities (which would blow up if bad shit went down) appropriately compensated investors for the inherent risk of the products. Of course, this wasn’t true, and it shouldn’t take a Wharton professor to realize that subprime securities were overpriced, offering yields that were too low relative to their risk.

Yet, an astute reader may claim, perhaps subprime yields do make sense when viewed over a longer time horizon. I beg to differ, and Taleb would certainly agree. As he and his followers have noted, even over the long run, investors can profit by buying assets that will pay off only under extreme occurrences. Put another way, banks inefficiently price insurance, selling it too cheap. As a result, few financial institutions have been able to survive in their current form for more than a half century. Yes, the credit crisis was undoubtedly a seminal series of events, but it wasn’t the first and likely won’t be the last apocalyptic era on Wall Street.

Unless markets do suddenly validate the EMH and institutions begin appropriately pricing extreme events, the financial world will continue to be beset by periodic collapses. Personally, I doubt anything will change. So, I advise you to chase some tail.