There was a lot of smoke and mirrors blowing immediately after the credit crisis looking for sources of blame. A book that made a lot of press was “The Quants” by Scott Patterson. Mr. Patterson was a WSJ reporter and clearly has a flare for the imaginative and while “The Quants” makes what is normally a quite dry subject (like accounting or actuarial science), an easy read and adds adventure to the quant story, there’s much in it that’s inaccurate, hyperbole and well, probably made up. Like the conversation between a waiter and Cliff Asness, and Peter Muller and Ken Griffin bickering. I mean, he presents their dialogue like a David Baldacci novel’s characters, fun, but highly fictional!
One of the main themes of the book however is really about how Wall Street whiz kids brought the house down because with their impetuous, brilliant and extremely aggressive nature, they made their fortunes by robbing less intelligent clients and their investors. While other quants using badly mis-specified models based on the normal curve (specifying default correlation among bonds for instance), underpriced risk and contributed to huge losses for the banks. If you took both exaggerations and divided them by 10, you’d probably reach something nearer the truth while the overall pain of losses was spread pretty much across all quants (except John Paulson) and non-quants during the credit crisis.
However, one good takeaway is that the book makes you think about whether quants have learned anything about major market turns and whether they’ve adapted their models and modeling techniques to consider the impact of “Obsidian Uncertainties” (i.e. formally Black Swans) and ELE events. The answer to that question is a stark “YES”. The first example of it comes with UCITS mandating VaR requirements for EU mutual funds to less than 4 breeches per year at 99% CI. In 250 trading days, 2.5 breeches of the 99% VaR is right on target. UCITS mandate therefore is a signal to quants to “tighten up” and FactSet’s Balanced Risk model considers that target specifically.
Another good example comes from the increasing usage of stress-testing one’s portfolio against variables that could move your portfolio toward larges losses. Thus, it’s no longer sufficient to create an Alpha model based on back-testing through turbulent periods alone, so now quants are examining their quantitatively derived portfolio behaviors by using covariance matrices from the past to forecast the risk from credit crises, LTCM debacles, Asian contagion security dependencies and so forth all of which involve situations where idiosyncratic risks take a back-seat to market risks in a major way.
Crises events are characterized by factor efficacy falling-off considerably while securities increase their correlation as well. When that has happened in the past, quants used to hold firm and wait for the correlative nature of the markets to return to pre-crisis levels and this stocks “de-correlation” meant factor efficacy was returning. Now however, quants have learned that these periods may persist for long periods of time and that one way of prepping your portfolio for these events is to examine forecasted risks from short horizon risk models (~1 year of daily values). In this way, turning or inflection points of the market are more quickly spotted than using a long horizon risk model (~60 months) and adjustments to the portfolio can occur by rotating more quickly to factor bets that are more efficacious in the new environment.The tricky part is, adaptation in one’s overall investment strategy due to market conditions is exactly what Ben Graham taught us not to do. During the technology bubble for instance, many value investors moved more toward growth only to go out of business when the bubble burst, besides introducing enough style drift that consultants fired them for that reason alone. Ben Graham’s philosophy is about maintaining investment process discipline and not reacting to the whims of Mr. Market. However, for the truly post-modern quant, adaptation is the discipline. From the quant’s perspective, application of the Ben Graham principles to the investment process is about adhering to risk mitigation “come hell or high water”. It’s about providing the portfolio with a margin of safety through the methods available in the quantitative art. The credit crises has truly allowed quants to leverage their methods and think about risk in new ways. This indeed has raised the IQ of the intelligent quantitative manager.