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.
Book Details:
- Author: Brian R. Brown
- ISBN: 9780470824887
- Year Published: 2009
- Pages: 256
- BISAC: BUS027000, BUSINESS & ECONOMICS/Finance
About the Book and Topic:
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.
Black-Box trading is a diverse and colorful niche within the financial industry, inclusive of differentiated investment strategies such as statistical arbitrage, market-neutral trading, high frequency market making, and algorithmic trading. Each flavor of “investing” competes with one another for price discrepancies and trading opportunities, essentially “chasing the same signals”. Over the past decade, the black-box phenomenon has had a coming of age, blossoming into an influential industry of liquidity providers – estimated at one third of all market turnover. This chronicle of Black Box trading profiles the evolution of quantitative trading, the academic foundations of their investment style and the catalysts of its rise to prominence. Chasing the Same Signals is not a book about what signals are being chased but rather a story on how they chase and compete for the same signals. It’s a story about financial innovations and how black-box traders have adapted to a dynamic market place. Is the party over or will Black Box evolve to inhabit a new landscape amidst the global financial crisis?
– Up to date information on a rarely published topic – There are only a handful of books published on this topic, yet the influence of Black Box trading is growing inexorably. – Key insights from a market professional – Author is a former VP of Morgan Stanley Asia with global experience in both IT and finance. – Strong media interest – As Black Box trading exerts and increasingly strong hold on the market, there will be growing demand for a book that explains the influence of these systems and the technology behind them.
About the Author
Brian Robert Brown, based in Hong Kong was formerly a Vice President of Sales & Trading at Morgan Stanley (Asia). During his stint in Morgan Stanley, he successfully established and led the systematic trading business and contributed to various regional market reforms. Before joining Morgan Stanley, Brian worked for Trout Trading Management, founded by legendary commodity trader Monroe Trout and one of the pioneers of black-box trading. Brian has been directly involved with many industry milestones in quantitative trading and has advised top-tier hedge funds on trading strategies. Brian graduated from the University of Waterloo in 1996 with appointment to the Dean’s Honor roll.