Chasing the Same Signals: How Black-Box Trading Influences Stock Markets from Wall Street to Shanghai
The worst stock market crash since Black Monday during October of 1987 occurred during the first week of August of 2007. But nobody noticed.
On the morning of August 6th 2007, investment professionals were baffled with unprecedented stock patterns. Mining sector stocks were up +18% but manufacturing stocks were down -14%. It was an extreme sector skew yet the S&P index was unchanged at +0.5% on the day. The next few days would continue with excessive volatility. MBI Insurance, a stock that had rarely attracted speculation would finish up +15% on Aug 6th, followed by another +7% on Aug 7th, and then finish down -22% over the subsequent two days. The brief rally in MBI was short lived.
Only weeks later would investors begin to have insights on the dispersion patterns. Prominent hedge funds that had never had a negative annual performance began disclosing excessive trading loses with many notable firms reporting several hundred millions were lost - in a single day. Hedge funds were hemorrhaging in excess of 30% of their assets when the S&P index was unchanged. The market dispersion was the side effects of the synchronous unwind ignited by the hordes of "computerized" strategies that were caught off guard when history didn't repeat. It was the industry's first world wide panic - by machines.
Over the past decade, computerized (or black-box) trading has had a coming of age. Black-box firms use mathematical formulas to buy and sell stocks. The industry attracts the likes of mathematicians, astrophysics and robot scientists. They describe their investment strategy as a marriage of economics and science. Their proliferation has been on the back of success, black-box firms have been among the best performing funds over the past decade, the marquee firms have generated double-digit performance with few if any months of negative returns.
Through their coming of age, these obscure mathematicians have joined the ranks of traditional buy-n-hold investors in their influence of market valuations. A rally into the market close is just as likely the byproduct of a technical signal as an earnings revision. They are speculated to represent a one third of all market volume albeit their influence to the day-to-day gyrations goes largely unnoticed. CNBC rarely comments on the sentiments of computerized investors.
Conventional wisdom suggests that markets are efficient, random walks and that stock prices rise and fall with the fundamentals of the company. How then have black-box traders prospered and how do they exploit market inefficiencies? Are their strategies on their last legs or will they adapt to the new landscape amidst the global financial crisis?
Chasing the Same Signals is a unique chronicle of the black-box industry's rise to prominence and their influence on the market place. This is not a story about what signals they chase, but rather a story on how they chase and compete for the same signals.