While not taking Mr. Zweig’s alliteration too literally, I still think he’s off-base. It’s a tall order to ask Mr. Zweig’s largely retail investor readership to gauge exactly when the “quality” fund boom will be over. One only needs to see the price action in Apple over the past six months to see how difficult it is to guess when a stock “bust” is over. Asking a retail investor to parse the popularity graph of an investing trend? While amateurs often out-perform the pros, I think this is too much to ask.
So I’ll simply end this with another excerpt from Mr. Zweig’s fine 2009 column, wherein a money manager calls data mining “one of the leading causes of the evaporation of money, especially in quantitative strategies."
Update (3/19) - Jason Zweig sent in the following response:
Backtesting typically has several undesirable characteristics: 1) it's conducted over relatively short time periods, often 10 years or less; 2) the "strategies" tested are often complex, featuring multiple variables weighted in unusual relationships to each other; 3) only one market or asset class is tested; 4) no theory accounts parsimoniously for the evidence.
In the case of the "quality" factor, however, these limitations aren't present. Novy-Marx went back to the 1960s, and both DFA and AQR extended the period back to 1926. The strategy tested was extraordinarily simple: revenue minus COGS divided by assets (adjusted for debt when financials are included). DFA and AQR have tested the strategy across large and small US stocks, as well as international and emerging markets stocks, over the longest time periods for which data are available. Finally, the results can be explained by fairly simple theories; for instance, investors might be behaviorally overweighting the predictability and importance of earnings, which are more salient and short-term than gross profitability.
For all of these reasons, I'm fairly confident these results aren't merely data-mined. They could be, but so could the value and size effects for that matter. I'd say it's not very likely.
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