You are previewing Chasing the Same Signals: How Black-Box Trading Influences Stock Markets from Wall Street to Shanghai.
O'Reilly logo
Chasing the Same Signals: How Black-Box Trading Influences Stock Markets from Wall Street to Shanghai

Book Description

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.

Table of Contents

  1. Copyright
  2. Acknowledgments
  3. 1. The Canary in the Coal Mine
    1. 1.1. THE SIGNAL OF IMBALANCE
    2. 1.2. THE CROWDED TRADE EFFECT
    3. 1.3. THE BLACK-BOX PHENOMENON
    4. 1.4. THE EVOLUTION OF QUANTS
    5. 1.5. WHAT SIGNALS ARE THEY CHASING?
    6. 1.6. THE SAME SIGNALS
  4. 2. The Automation of Trading
    1. 2.1. THE LEGEND OF DoCoMo MAN
    2. 2.2. COMPUTER-TO-COMPUTER TRADING
    3. 2.3. THE LIBERALIZATION OF U.S. EQUITY MARKETS
    4. 2.4. THE IMPACT OF TECHNOLOGY
    5. 2.5. A SYSTEMATIC INDUSTRY
  5. 3. The Black-Box Philosophy
    1. 3.1. THE MARRIAGE OF SCIENCE AND ECONOMICS
      1. 3.1.1. Econometrics
      2. 3.1.2. Microstructure Research
      3. 3.1.3. Optimization and Execution
    2. 3.2. THE CULTURAL DIVIDE
      1. 3.2.1. Measure, Manage, and Model
    3. 3.3. THE BLACK-BOX COMMUNITY
    4. 3.4. THE COMING OF AGE
  6. 4. Finding the Footprint
    1. 4.1. STATISTICS AND ARBITRAGE
    2. 4.2. THE LAW OF LARGE NUMBERS
    3. 4.3. INSIDE THE ORDER BOOK
    4. 4.4. A GAME OF MILLISECONDS
    5. 4.5. LIQUIDITY PROVIDERS AND MARKET EFFICIENCY
  7. 5. Disciples of Dispersion
    1. 5.1. ECONOMETRIC RESEARCH
    2. 5.2. MARKET-NEUTRAL STRATEGIES
    3. 5.3. WINNERS AND LOSERS
    4. 5.4. RISK FACTOR MODELS
    5. 5.5. THE LEVERAGE EFFECT
    6. 5.6. THE DISPERSION EFFECT
  8. 6. The Arms Race
    1. 6.1. THE SUPPLIERS AND DEMANDERS OF LIQUIDITY
    2. 6.2. THE SIGNIFICANCE OF MARKET STRUCTURE
    3. 6.3. THE SIGNIFICANCE OF TRANSACTION COSTS
    4. 6.4. THE ERA OF ALGOS
    5. 6.5. THE FRAGMENTATION OF LIQUIDITY
    6. 6.6. THE LONG TAIL OF MARKET IMPACT
  9. 7. The Game of High Frequency
    1. 7.1. THE MOST ACTIVE INVESTORS
    2. 7.2. THE SPREAD
    3. 7.3. PREDATORS, SPECULATORS, OR INVESTORS
      1. 7.3.1. Pinging the Book
      2. 7.3.2. Predatory Algorithms
      3. 7.3.3. The Rebate Structure
    4. 7.4. THE COMPETITION FOR LIQUIDITY
  10. 8. The Russell Rebalance
    1. 8.1. THE RUSSELL RECONSTITUTION
    2. 8.2. THE IMPACT OF TRACKING RISK
    3. 8.3. THE GUARANTEED TRADE
    4. 8.4. THE RUSSELL EFFECT
    5. 8.5. THE CLOSING PRICE
  11. 9. The Ecology of the Marketplace
    1. 9.1. THE CASH BUSINESS
    2. 9.2. TRENDS IN ORDER SEGMENTATION
    3. 9.3. BEST-EXECUTION MANDATES
      1. 9.3.1. Unbundled Research
      2. 9.3.2. Boutique Research
    4. 9.4. THE EVOLUTION OF LIQUIDITY
  12. 10. Globalization of Equity Markets
    1. 10.1. GLOBALIZATION OF TRADING STRATEGIES
      1. 10.1.1. The Technology Gap
    2. 10.2. THE GLOBAL LANDSCAPE
      1. 10.2.1. European Markets
      2. 10.2.2. Asian Markets
    3. 10.3. DIVERSITY OF EQUITY MICROSTRUCTURE
      1. 10.3.1. Costs of Trading
      2. 10.3.2. Market Access
    4. 10.4. REGULATORY RISK
  13. 11. An Adaptive Industry
    1. 11.1. THE DECAY EFFECT
    2. 11.2. THE SEARCH FOR SIGNALS
      1. 11.2.1. Weather Data
      2. 11.2.2. Location Data
      3. 11.2.3. Search Data
    3. 11.3. ECONOMIC CHALLENGES
      1. 11.3.1. Short-Sell Restrictions
      2. 11.3.2. The Cost of Borrowing
      3. 11.3.3. Market Structure
      4. 11.3.4. Investor Behavior
    4. 11.4. ADAPTIVE MACHINE THEORY
  14. 12. Conclusion
  15. Notes
    1. Chapter 1: Canary in the Coal Mine
    2. Chapter 2: The Automation of Trading
    3. Chapter 3: The Black-Box Philosophy
    4. Chapter 4: Finding the Footprint
    5. Chapter 5: Disciples of Dispersion
    6. Chapter 6: The Arms Race
    7. Chapter 7: Game of High Frequency
    8. Chapter 8: The Russell Rebalance
    9. Chapter 9: Ecology of the Marketplace
    10. Chapter 10: Globalization of Stock Markets
    11. Chapter 11: An Adaptive Industry