Marketwatch.com reports that Goldman Sachs‘ Global Alpha hedge fund is down 26% this year-to-date.
John Carney at DealBreaker.com passes along a ‘Dear Investor’ letter from Jim Simons‘ Renaissance Technologies fund that discloses notable losses in August.
Katherine Burton and Jenny Strasburg at Bloomberg.com have further detail on this ‘quant bloodbath.’
Now that we know many quantitatively driven investment firms have taken big hits, what does it all mean?
Kaja Whitehouse at WSJ.com quotes Lehman Brothers’ Matthew Rothman who has been taking note of the extraordinary stresses the current market has been putting on quantitative investment models and those that invest in them.
“Wednesday is the type of day people will remember in quant-land for a very long time,” said Mr. Rothman, a University of Chicago Ph.D. who ran a quantitative fund before joining Lehman Brothers. “Events that models only predicted would happen once in 10,000 years happened every day for three days.”
Paul Kedrosky at Infectious Greed notes that this quant meltdown raises the issue of “fat tails” and the idea that we are experiencing something altogether unpredictable. Kedrosky looks at this question another way.
So, the real message is that fat-tails is the wrong way to think about things. Stocks, generally speaking, alternate between two modes: one that can be usefully and profitably modeled using distributions; and another mode that is essentially distributionless, with all stocks moving together and then apart like a school of tiny fish responding to a predator. These are species (no pun intended) of regime change in models, and the lesson for me is that most quant models are no better than ever at detecting such changes and responding accordingly.
It could also be the case that some eventualities are beyond the scope of quantitative models. Michael Santoli at Barrons.com quotes one manager:
Says one quant manager caught in this whipsaw: “There is this unknown risk, when there are enough people doing what you do, that when some of them have to unwind and they start unwinding — you are just going to get crushed. And that’s not in the model anywhere.”
Zero Beta looks to leverage as being a culprit. Given the prior success of some of these quantitative models, some investors have felt more comfortable leveraging these programs, to disastrous effect.
The models themselves, as predictive in isolation as they may have been, once put into practice by others becomes more and more useless. The effect of increasing leverage acts to magnify what may be diminishing expected gain until of course it becomes a loss, which then is magnified quickly – convergence is finite, but divergence infinite in theory.
The previously mentioned articles list a whole host of reasons for this ‘quant bloodbath.’ The fact of the matter is that every investment approach will go through periods of underperformance. It is inevitable. No approach is immune: deep value investors, growth investors, trend followers, chart readers or the aforementioned quants.
It may be some time before we have a clear understanding of what went wrong in this most recent episode. We have previously written on the use of quantitative mutual funds and quantitative methods. The best quantitative investors use the models to quantify and automate theoretically sound investment theories. Models are advantageous in that they allow investors to consistently and quickly analyze a host of securities according to a (presumably) well though-out investment process.
However, things change in the capital markets – sometimes temporarily and sometimes permanently. Quantitative investors are like all other investors in that sometimes their methods stop working. Leverage, not even excessive leverage, can make riding out periods of underperformance all the more difficult. The question that arises for quants: Is it the model or the market? All over Wall Street they are pondering that very question.
*The title of this post was inspired by the fine 1988 David Mamet movie, Things Change starring Don Ameche and Joe Mantenga.