As George Bernard Shaw observed: "All professions are conspiracies against the laity." That observation applies particularly to the mysterious and arcane world of quantitative trading.
Put simply, quantitative trading uses complex computer models to make trading decisions based on historical models that extrapolate past patterns into the future. Sophisticated computer algorithms spot opportunities to buy and sell securities — exploiting very small price differences. These differences are then leveraged up — leading to often eye-popping returns. As small armies of "quants" emerged from the hallowed halls of academia, quantitative strategies have become widespread across both traditional asset managers and hedge funds. The result has been that the biggest and most liquid financial markets in the world now are traded by computers with little if any human intervention.
Quakes in Quantitative Trading: Goldman Tarnished
Quantitative trading has been a terrific — and profitable — boon to Wall Street. But recent market turmoil has revealed some startling weaknesses in this real world video game style of trading. This past week, none other than Goldman Sachs, one of the savviest players in finance, revealed huge losses in its quant-driven Global Equity Opportunities funds. The collapse was startling in its quickness. On Monday, the fund was down a few percentage points from the beginning of the year. By Friday, it had lost more than 30% of its value.
Although the exact details are unclear, shares began to move in ways that were precisely the opposite of those predicted by computer models. These moves triggered selling by funds as they attempted to cover their losses and meet margin calls from banks. This, in turn, made share price movements even worse. As Goldman’s CFO noted in a rare conference call: "We are seeing things that were 25-standard deviation events, several days in a row." That’s something that only happens once every 100,000 years.
With its flagship GEO fund teetering on the edge of collapse, Goldman committed $2 billion of its own capital to bailout the fund. The failure of such a large fund would have been a huge embarrassment to Goldman. And among the losers would have been Goldman partners, a significant number of which are thought to have been investors in the fund.
Highly respected Renaissance Technologies suffered similar woes. Founder James Simons wrote investors that "we cannot predict the duration of the current environment," even as he revealed startling losses in its funds, including Medallion, which has had an annual return of 30% since 1988. As Lehman Brothers noted last week: "Models (ours including) are behaving in the opposite way we would predict and have seen and tested for over very long time periods,"
Quakes in Quantitative Trading: Three Achilles’ Heels
The troubles experienced by quant funds over the past few weeks is just one of the regular reminders that Mr. Market gives quants that their models work very well — until they don’t. At that point, the models tend to collapse with devastating consequences. Here’s why.
First, for all their bells and whistles, quant models are inherently flawed. It turns out that "rare" events aren’t so "rare" after all. The collapse of the Goldman fund is just a reprise of the collapse of Long Term Capital Management (LTCM) in 1998. Recall that LTCM’s whiz kids, who included some Nobel prize-winning economists, had devised model-based trading strategies that also went south. And with quant models predicting the future on the basis of past data, ironically it’s the benign conditions of the past few years that have led to the biggest distortions between predictions and reality. And no quant model can account for "Black Swan" events — those few events that make all the difference.
Second, market players assume a level of liquidity that just isn’t there in times of panic. When someone yells "fire" in the global financial market theater, too many players head for the exit doors at once. And the low interest rate, low-return environment of the past few years prodded many investors to go into less liquid assets to generate higher returns. And short-term investors, facing a liquidity crisis, have trouble exiting when they want to raise cash.
Third, good times breed greed or — in financial terms — an appetite for leverage. Goldman’s fund was leveraged 6x before Monday’s bail-out. As other highly leveraged investors cut debt, they unwind positions, forcing them to sell stocks at fire sale prices. Asymmetric pay structures — "heads I win, tails you lose" — also give hedge fund managers an incentive to take on too much risk.
The elephant in the room is investor psychology — that elusive variable that can never make it into even the most sophisticated of quant models. Yet plain old common sense tells us that when investors get frightened, they sell indiscriminately. The only real surprise is that this surprises the quants.
Quakes in Quantitative Trading: The Only Accurate Prediction
Here’s what’s even more surprising. Looked at through the lens of financial history, the events of the last few weeks aren’t even all that serious. In the second to last week of July, U.S. junk debt yields jumped by 50 basis points. Yet since the end of 1986, a weekly rise or fall of at least 50 basis points has been seen no fewer than 37 times — though, admittedly, some of the price moves in mortgages have been far more severe.
Indeed, the only prediction about quant strategies that always rings true is predictions of their inevitable demise. Pick up a copy of Nassim Nicholas Taleb’s first book, "Fooled By Randomness," and you’ll find a startlingly accurate description of John Devaney, the hedge fund manager who went bust after a bad bet on subprime mortgage assets and now is selling his 142-foot yacht for $23.5 million. Although the book was published in back October 2001, Taleb describes both the Devany-like character and the nature of the financial blow up with startling accuracy.
There is, indeed, nothing new under the financial sun.
Nicholas A. Vardy
Editor, The Global Guru
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