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An explanation for the Quant Meltdown?
E. Khandani and Andrew W. Lo, two financial engineers at M.I.T, have written a paper on the August 2007 Quant Meltdown.This is a paper that should give quants a great deal of comfort.Even better, it should give those quants hurt by the meltdown an excuse.Whether or not this paper should give them comfort, much less an excuse, is another matter entirely. For reasons of clarity, in this paragraph, I have slightly rewritten one of Khandani and Lo’s central arguments. Table three in their paper gives daily returns for a Lo and MacKinlay contrarian trading strategy applied to all U.S. common stocks. The authors believe that this strategy is representative of the quant strategies that suffered in August.The table provides ROR data for all such common stocks (and also for market-cap deciles) in the University of Chicago's CRSP Database from Monday, July 30 to Friday, August 31, 2007.The three days in the second week August 7th, 8th, and 9th are outliers, with losses of 1:16%, 2:83%, and 2:86%, respectively, yielding a cumulative three-day loss of 6:85%.Although this three-day return may not seem that significant especially in the hedge-fund world, it is a loss of 12 daily standard deviations from the norm!Moreover, many long/short equity managers were employing leverage; hence their realized returns were magnified several-fold.Curiously, a significant fraction of the losses was reversed on Friday, August 10th, when the contrarian strategy yielded a return of 5:92%, which was another extreme outlier of 11.4 daily standard deviations. In fact, the strategy's cumulative return for the entire week of August 6th was 0:43%, not an unusual weekly return in any respect. This reversal is a tell-tale sign of a liquidity trade. By liquidity trade Khandani and Lo mean that someone with statistical arbitrage positions was forced to unwind their trades for unknown reasons, but for reasons that, presumably, had nothing to do with financial merits of the trades themselves. But was it really a liquidity trade?If it was then we have an excuse. In which case, the August meltdown was not an evil portent; it was not the sign of a coming quant apocalypse.On the positive side, it explains most of the available evidence.More important, it is hard to think of an alternative theory other than something bad happened and we don’t know what. On the negative side, the fact that we don’t have a good alternative theory means only that we may have to use the theory we have.It does not mean that the theory is right. It does not mean that we really know what is going on.There are a lot of bad things we don’t understand or understand poorly.Cancer, for example.More, the authors do not say who, exactly, unwound these positions and, strictly speaking, this is the only kind of evidence that would confirm their theory.More important, the fact that they do not mention any candidates is evidence against their theory.Wall Street runs on gossip.Trying to find the guilty party, if one exists, should be should take an hour’s to a week’s work and the meltdown was weeks ago. Khandani and Lo seem to understand these issues, at least in part.For example, at one point early in the paper they write, “We wish to emphasize at the outset that these hypotheses are tentative, based solely on indirect evidence, and without the benefit of very much hindsight given the recency of these events.”This is quite good, but it does not go far enough.Fantasy writer R. A. Lafferty gets it exactly right when he writes, “A myth is the highest statement of scientific fact, if it is the only statement of scientific fact.”I sometimes call this, “poker quality information.”It is information that may not be true, but is still worth betting on.On this basis, I would not close positions in quant funds.Not incidentally, I do not mean that every piece of information should be given some weight.There is no lower limit to how bad information and analysis can get.Witness the editorial columns in the Wall Street Journal, for example.In one of his novels, Lafferty (my Lafferty quotes are from memory) says, “You think believing in ghosts is odd?You should hear some of the things ghosts believe in!”Lafferty was joking.That’s more than I can say about some of the stuff I read about quantitative analysis.
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