You Can't Measure Alpha Independent of Risk

When I teach investments, there's always a section on market efficiency. A key point I try to make is that any test of market efficiency suffers from the "joint hypothesis" problem - that the test is not tests market efficiency, but also assumes that you have the correct model for measuring the benchmark risk-adjusted return.

In other words, you can't say that you have "alpha" (an abnormal return) without correcting for risk.

Falkenblog makes exactly this point:

In my book Finding Alpha I describe these strategies, as they are built on the fact that alpha is a residual return, a risk-adjusted return, and as 'risk' is not definable, this gives people a lot of degrees of freedom. Further, it has long been the case that successful people are good at doing one thing while saying they are doing another.

Even better, he's got a pretty good video on the topic (it also touches on other topics). Enjoy.

Dilbert On Mutual Funds

Nuff said.

A Good Paper on "Return Factors"

Robert Haugen is one of (if not THE) best-known figure in the behavioral finance (i.e. "markets are not efficient") camp. He wrote one of the earliest books on the topic in 1995 (The New Finance) and runs a quantitative finance shop based on much of his research. In a recent paper with Nardin Baker of UC-Irvine, he examines the explanatory and predictive ability of a wide array of observable factors. Here's the abstract

This article provides conclusive evidence that the U.S. stock market is highly inefficient. Our results, spanning a 45 year period, indicate dramatic, consistent, and negative payoffs to measures of risk, positive payoffs to measures of current profitability, positive payoffs to measures of cheapness, positive payoffs to momentum in stock return, and negative payoffs to recent stock performance. Our comprehensive expected return factor model successfully predicts future return, out of sample, in each of the forty-five years covered by our study save one. Stunningly, the ten percent of stocks with highest expected return, in aggregate, are low risk and highly profitable, with positive trends in profitability. They are cheap relative to current earnings, cash flow, sales, and dividends. They have relatively large market capitalization and positive price momentum over the previous year. The ten percent with lowest expected return (decile 1) have exactly the opposite profile, and we find a smooth transition in the profiles as we go from 1 through 10. We split the whole 45-year time period into five sub-periods, and find that the relative profiles hold over all periods. Undeniably, the highest expected return stocks are, collectively, highly attractive; the lowest expected return stocks are very scary - results fatal to the efficient market hypothesis. While this evidence is consistent with risk loving in the cross-section, we also present strong evidence consistent with risk aversion in the market aggregate's longitudinal behavior. These behaviors cannot simultaneously exist in an efficient market.

Here are some of the factors that they find statistically significant:

• Price Multiples such as price to cash flow, sales, book value, and earnings (negative relationship with subsequent returns
  
• Profitabiliy measures such as ROE, ROA, and Profit Margins (positive relationship)
• Volatility in returns, whether "raw" or "residual" (negative relationship)
• Momentum (positive relationship)
• Recent returns (positive rel;ationship with last year's return, negative with last month's return, and last month's "residual" return)

Read the whole thing here

It's worth reading. Haugen is clearly not an ubiased observer (he does run a shop based on the idea that markets are inefficient), and there's definitely some serious data mining going on here. Having said that, it's definitely worth reading. It gives a very good summary of many of the factors that prior research has found to be significantly related to subsequent returns. I'll be making the next group of student in Unknown University's student-managed fund read it.

HT: Empirical Finance Research

Information Traders Must Be Compensated

I'm still in the thick of exams week (one to give today, one Friday, and one Saturday), and they're not all written yet. But this piece from Burton Malkiel in FT.com was worth highlighting. The best part was the last paragraph:

As de facto market makers, high-frequency traders can exploit pricing anomalies and pick up pennies at the expense of other traders. Such activities are not sinister. The paradox of the efficient market hypothesis is that the people whose trades help make the market efficient must be compensated for their efforts. As former SEC Chairman Arthur Levitt has written: “We should not set a speed limit to slow everyone down to the pace set by those unwilling or unable to compete.” High-frequency trading networks let large and small investors enjoy a more efficient and less costly trading environment.

Read the whole thing here.

HT: Abnormal Returns

How Can Markets Be Effificent If People Are such Morons

The always enjoyable Megan McArdale has a great piece explaining the EMH with the above title in The Atlantic.com. There's also a pretty good snark-war in the comment section between a trader who insists markets are easily beatable and someone else who pretty much shoots him to pieces.

Read it, and give it to your students.

Bill Miller: The Stock Picker's Defeat

From 1991 to 2005, Bill Miller (superstar mutual fund manager for Legg Mason's Value Trust) beat the S&P every year - a record no other manager has ever come close to matching. Then, this last year the bottom fell out and his fund lost 58% (about 20% more than the typical fund.

The Wall Street Journal has a great interview of Miller, and here's the best line:

This meltdown has provided a lesson for Mr. Miller and other "value" investors: A stock may look tantalizingly cheap, but sometimes that's for good reason.

It's a very good piece for discussing in class, since it touches on a lot of issues related to market efficiency. Read the whole thing here.