Quants: How Math Wizards Made Billions and Nearly Crashed the Stock Market — Scott Patterson
A book about how a whole layer of "smart money" emerged on Wall Street—quant funds whose models set the pace of the market for years, and in times of stress revealed the vulnerabilities of the entire system.
This is not a textbook of formulas, but a report with names and details: from the rise of AQR, Citadel, Renaissance to a chronicle of the events of August 2007, when everything went wrong.
The author assembles a picture from dozens of interviews and internal episodes, showing where the “magic” of models ends and the reality of risk management .
Patterson writes in simple language, but sticks to the facts: how assets under management accumulated, why "common signals" and identical assumptions in risk models lead to the simultaneous actions of thousands of participants, and how the belief in "statistically impossible" crashes ended.
The result is an honest history of an industry that taught markets discipline and automation—and at the same time reminded them of the cost of making difficult assumptions.
What the book is about (briefly): a chronicle of the emergence and stress of the quant approach: PDT/Morgan Stanley (Peter Mueller), Citadel (Ken Griffin), AQR (Cliff Asness), desk Deutsche Bank (Boaz Weinstein), the Renaissance phenomenon.
The focus is on strategies, risk management, liquidity and signal crowding.
When it will be useful in practice:
- Portfolio risk management . To check whether leverage/liquidity in models is overstated and how correlations on a "thin" day.
- Strategy audit and overcrowding . To recognize common signals and understand how mass deleveraging turns backtesting into an illusion.
- Stress testing . August 2007 scenarios as a template for own-risk tests and regulatory questions for strategy providers.
- Building a product showcase . What questions to ask hedge funds/quant management companies about model assumptions, alpha sources, and liquidity management.
- ATS development/operation . A sober "checklist" of hypotheses and failure modes: where the fine points lie in high-frequency and systematic value/momentum.
- Team training and content . Case studies for internal reviews, interview preparation, and educational materials without unnecessary math.
- Investment decisions for private investors . Understanding the limits of "black boxes" and a sober assessment of promises of "stable alpha" in fund advertising.
Suitable for: investors and traders who want to understand the strengths and weaknesses of the quantitative approach; risk/PM teams building control procedures; anyone who needs a human perspective on the modeling industry without an overload of formulas.
