Black Box Trading: Why They All “Blow-Up” by Global Slant
“We Are All Doing The Same Thing”
I recently listened to a podcast with some all-star [there are awards for everything now] “Black Box” equity trader. It was quite a “telling” interview & I thank him for his insights but I’d heard it all before. His confidence was staggering considering the general unpredictability of the future and, of course, the equity markets. He explained how he had completely converted from a generally unsuccessful, discretionary technical trading style to a purely quantitative and scientific trading mode. He seemed to be so excited that his models, according to him, were pretty much “bullet proof”. Having had more than just some tangential experience with black box modeling and trading myself I thought…you know…some people will just never learn.
Black Box Trading
You see some years ago I was particularly focused on quantitative investing. Basically, “screw” the fundamentals and exclusively concentrate on price trends/charts and cross security/asset correlations [aka “Black Box” trading]. I was fascinated with the process and my results were initially stellar [high absolute returns with Sharpe Ratios > 2.0]. And, after looking at the regression data many others agreed. I was in high demand. So I “made the rounds” in Manhattan and Greenwich to a group of high profile hedge funds. It was a very exciting time for me as the interest level was significant.
As it turned out I had the good fortune of working with one of the world’s largest and best performing hedge funds. Their black box modeling team had been at it for years…back-testing every conceivable variable from every perceived angle…twisted/contorted in every measurable manner…truly dedicated to the idea that regression tested, quantitative trading models were the incremental/necessary “edge” to consistently generate alpha while maximizing risk-adjusted, absolutely positive returns. We worked together for some time and I became intimately involved with their quantitative modeling/trading team…truly populated with some of the best minds in the business.
While in Greenwich Ct. one afternoon I will never forget a conversation I had with a leading quantitative portfolio manager. He said to me that despite its obvious attributes “Black Box” trading was very tricky. The algorithms may work for a while [even a very long while] and then, inexplicably, they’ll just completely “BLOW-UP”. To him the most important component to quantitative trading was not the creation of a good model. To him, amazingly, that was a challenge but not especially difficult. The real challenge, for him, was to “sniff out” the degrading model prior to its inevitable “BLOW-UP”. And I quote his humble, resolute observation “because, you know, eventually they ALL blow-up“…as most did in August 2007.
It was a “who’s who” of legendary hedge fund firms that had assembled “crack” teams of “Black Box” modelers: Citadel, Renaissance, DE Shaw, Tudor, Atticus, Harbinger and so many Tiger “cubs” including Tontine [not all strictly quantitative but, at least, dedicated to the intellectual dogma]…all preceded by Amaranth in 2006 and the legendary Long Term Capital Management’s [“picking up pennies in front of a steam-roller“] demise one decade earlier.
Years of monthly returns with exceedingly low volatility were turned “inside out” in just 4-6 weeks as many funds suffered monthly losses > 20% which was previously considered highly improbable and almost technically impossible…and, voila…effectively, a sword was violently thrust through the heart of EVERY “Black Box” model. VaR and every other risk management tool fell victim to legitimate liquidity issues, margin calls and sheer human panic.
Many of these firms somehow survived but only by heavily gating their, previously lightly-gated, quarterly liquidity provisions. Basically, as an investor, you could not “get out” if you wanted to. These funds changed the liquidity rules to suit their own needs…to survive…though many did fail.
Anyway…to follow up on my dialogue with the esteemed portfolio manager…I asked “why do they all “BLOW-UP”? What are those common traits that seem to effect just about every quantitative model despite the intellectual and capital fire-power behind them? And if they all eventually “BLOW-UP” then why are we even doing this?”
He answered the second part of the question first…and I paraphrase…“We are all doing this because we can make a lot of money BEFORE they “BLOW-UP”. And after they do “BLOW-UP” nobody can take the money back from us.” He then informed me why all these models actually “BLOW-UP”. “Because despite what we all want to believe about our own intellectual unique-ness, at its core, we are all doing the same thing. And when that occurs a lot of trades get too crowded…and when we all want to liquidate [these similar trades] at the same time…that’s when it gets very ugly.“. I was so naive. He was so right.
Exactly What Were We All Doing?
We all knew what the leaders wanted and, of course, we wanted to please them. Essentially they wanted to see a model able to generate 4-6% annual returns [seems low, I know, but I’ll address that later]…with exceptionally low volatility, slim draw-down profiles and winning months outweighing the losing months by about 2:1. They also wanted to see a model trading exceptionally liquid securities [usually equities].
Plus the model, itself, had to be completely scientific with programmable filtering and execution [initiation and liquidation] features so that it could be efficiently applied and, more importantly, stringently back-tested and stress-tested . Long or short did not really matter. Just make money within the parameters. Plus, the model had to be able to accommodate at least $100M [fully invested most of the time as cash was not an option] and, hopefully, much more capital. This is much easier said than done but, given the brainpower and financial resources, was certainly achievable.
This is what all the “brainpower” learned…eventually.
First of all, a large number of variables in the stock selection filter meaningfully narrowed the opportunity set…meaning, usually, not enough tickers were regularly generated [through the filter] to absorb enough capital to tilt the performance meter at most large hedge funds…as position size was very limited [1-2% maximum]. The leaders wanted the model to be the hero not just a handful of stocks. So the variables had to be reduced and optimized. Seemingly redundant indicators [for the filter] were re-tested and “tossed” and, as expected, the reduced variables increased the population set of tickers…but it also ramped the incremental volatility…which was considered very bad. In order to re-dampen the volatility capital limits on portfolio slant and sector concentration, were initiated. Sometimes market neutral but usually never more than net 30% exposure in one direction and most sectors could never comprise more than 5% of the entire portfolio. We used to joke that these portfolios were so neutered that it might be impossible for them to actually generate any meaningfully positive returns. At the time of “production” they actually did seem, at least as a model, “UN-BLOW-UP-ABLE” considering all the capital controls, counter correlations and redundancies.
Another common trait of these models that was that, in order to minimize volatility, the holding periods had to be much shorter than a lot of us had anticipated. So execution [both initiation and liquidation] became a critical