Efficient Frontier
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William J. Bernstein

The Empty Chalice

S.W.I.N.E.

When I reflect on how much we can be certain of in finance, I’m reminded of Li’l Abner’s famous 1960s protest group: Students Wildly Indignant about Nearly Everything (which most readers of a certain age will remember).

Change "Indignant" to "Ignorant" and you pretty well sum up the state of knowledge in financial economics. Let’s face it, finance is a science in the same way that home economics is economics. The essence of a science is the presence of reasonably reproducible phenomena, and nothing (and I do mean nothing), is reproducible in finance. In the hall-of-mirrors world of investing, the fact that something was true in the past strongly suggests that it will not be true going forward. You say that stock returns are lowest on Mondays? Perhaps this was so, but as it became well known, enough investors saved their buying for the blue day (including myself), and this peculiar calendar quirk disappeared.

And that’s even before we consider September 11th-type shocks. As we found out all too clearly, geopolitical events beyond our control can take hold of the financial markets and shake them like beans in a castanet. This is nothing new. Consider these words of wisdom from Keynes’ General Theory, discussing economic "uncertainty":

The sense in which I am using the term is that in which the prospect of a European war is uncertain, or the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention . . . About these matters, there is no scientific basis on which to form any calculable probability whatever. We simply do not know!

Too bad Meriwether, Scholes, and their merry band hadn’t read this before they nearly blew up the world economy in 1998.

I find myself increasingly the recipient of a wide variety of questions regarding the behavior of asset classes and portfolios, and in almost all cases end up saying, "I simply do not know!" (Then perhaps adding, with a soupçon of rationalization, "And I don’t feel bad about it, because I don’t think anyone else does either.")

So I’ve decided to divide the Big Questions in investing into three categories: those we definitely know the answer to, those we definitely don’t, and those reasonable people can argue about.


What We Do Know

  1. Risk and return are strongly related. This, in fact, is the prime directive of finance. Although not formalized by Sharpe and Markowitz until decades ago, it was well known to the ancients, who charged good credits lower rates of interest than bad credits or upped rates in time of war and disorder. It’s backed by an enormous body of empirical data, both here and abroad: safe assets, such as short bonds and time deposits, over long enough periods always have lower returns than riskier assets, such as stocks. And, like all concepts with airtight empirical backing, it is also intuitively obvious: if two assets throw off the same amount of income, the safer one will sell for the higher price and thus a lower yield.

  2. The net return of speculation is zero. Bachelier’s famous dictum is axiomatic; there is no net benefit to the two individuals on opposite sides of a transaction. Taking this one step further, it is only possible to profit from a trade when you know more than the person on the other side. Over 70 years of empirical data show us that trading superiority, for all practical purposes, does not exist—that is, the markets are efficient.

  3. Costs matter. Your net investment return must of necessity be the aggregate return of the securities you own minus your expenses, including those caused by the market impact of your trades.

  4. Of the three major relative stock-asset-class characteristics—return, correlation, and volatility—only the latter seems to have any predictive value. That is to say, over the next five years, we can be reasonably certain that Turkish stocks will be riskier than U.S. stocks. On the other hand, we cannot say with certainty whose returns will be higher or lower. Correlation is an intermediate case: relative correlations—the higher value of U.S./France versus Turkey/France—will likely persist as well, but not with as much certainty as volatility.

That’s it. Four things.


What We Do Not Know, And Never Will

  1. Where is the market going tomorrow? We have more than 70 years of data on this one too. No one knows. And if someone does, she ain’t talkin’.

  2. Which securities should I own? The market can be thought of as an enormous computer whose job is to amalgamate all of the available information, both public and private, into extremely accurate security prices. The only way you can beat it, is if you are privy to non-public information or smarter than all of the other market participants. If you believe that either of these is true, then either your name is Ken Lay or you are an overconfident buffoon (or both).

  3. What’s the optimal future portfolio composition? This is the big kahuna of the portfolio analyst and it is absolutely unobtainable, since it is basically a variant of points one and two above. Yes, it is theoretically possible to calculate the optimal portfolio at any degree of risk if you know return, risk, and correlation. Unfortunately, the least predictable of these—return—is also the most critical to the calculation. The net effect on your wealth of feeding historical data into any portfolio black box, whether you’re simply backtesting, optimizing, or (drum roll, please) resampling, is about what you would get by tossing raw lumber into the intake of a jet engine.

In this list, there’s a paradox associated with every item. With the first and second cases, if you actually knew the answer, you would shortly become one of the world’s wealthiest people and surely wouldn’t be squinting into your monitor reading me. In the last case, if you knew the future returns of all assets, you wouldn’t need optimization or any other technique. You’d simply buy the highest-return asset and go to the beach.

Finally, I include here the most common specific question I get asked: Is there a role for a mid-cap allocation in an efficient portfolio? I don’t know; no one does.


What Reasonable People Can Argue About

These are what physicists call Deep Questions; if you know the answer to any of the following, please drop me a line:

  1. Is there a value effect? Personally, I think the answer is yes, as you can see from an accompanying piece. But there are some very smart people who disagree, one of whom is named Bogle. You quickly learn that when you disagree with the Sage of Valley Forge, you usually wind up cleaning egg off your face.

  2. Do small stocks have higher returns than large stocks? See point one above, then erase 80% of the empirical support.

  3. Do retained earnings increase earnings growth? You’d think that each percent of retained earnings produces a percent of extra return. But it very well may not. In this regard, REITs can be considered an experiment of nature in which Congress mandated that 90% of a whole sector’s earnings wind up in investor’s pockets. From January 1975 through April 2002, REITs have bested the S&P by 1.34% per year, truly remarkable when you realize that the latter have tripled in valuation in the interim, whereas the former have not budged their PEs or yields in the intervening 27 years. But it’s hard making judgments on just one sector. This is a testable hypothesis, of course—one could sort the CRSP by payout ratio and adjust for size and value. But that smacks of real work, which my doctor tells me to rigorously avoid.

  4. Is the historical equity risk premium useful in predicting the forward risk premium? I think not; there are numerous instances where very long periods of high/low risk premia reversed for equally long subsequent periods, such as bonds in the 19th and 20th centuries. More to the point, very high/low risk premia imply very high/low prices, which certainly do not imply subsequent high/low returns. But what do I know? I don’t have an endowed chair at Yale.

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