From the Publisher
Firsthand accounts from the people who were swept into, and then helped fashion, today's "quant-driven," dynamic world of finance. Quants are the backbone of today's investment industry. Their mathematical models are now the basis for most financial market innovations, such as exotic derivatives, structured investment products, quantitative trading strategies, and portfolio selection. Their spectacular successes and failures have become part of market folklore. But what they do, and how they do it, is often as opaque and hard to understand as the formulas they create. In How I Became a Quant, more than two dozen quants tell their war stories and detail the unexpected paths they have followed from the halls of academia to Wall Street, revealing the faces behind the quant revolution.
Richard R. Lindsey, PhD, MBA (New York, NY) is President of Bear, Stearns Securities Corporation. He is chair of the executive board of the IAFE. Barry Schachter, PhD (New York, NY) is Director of Quantitative Resources at Moore Capital Management. He is on the advisory board of the IAFE.
Table of Contents
Acknowledgments.
Introduction.
Chapter 1: David Leinweber, Leinweber & Co.
Chapter 2: Ronald N. Kahn, Global Head of Advanced Equity Strategies, Barclays Global Investors.
Chapter 3: Gregg E. Berman, Vice Chairman, RiskMetrics Group.
Chapter 4: Evan Schulman, Chairman, Upstream Technologies, LLC.
Chapter 5: Leslie Rahl, President, Capital Market Risk Advisors.
Chapter 6: Thomas C. Wilson, Chief Insurance Risk Officer, ING Group.
Chapter 7: Neil Chriss, Managing Director of Quantitative Strategies, SAC Capital Management, LLC.
Chapter 8: Peter Carr, Head of Quantitative Financial research, Bloomberg.
Chapter 9: Mark Anson, CEO, Hermes Pensions Management Ltd.; CEO, British Telecommunications Pension Scheme
Chapter 10: Bjorn Flesaker, Senior Quant, Bloomberg L.P.
Chapter 11: Peter Jäckel.
Chapter 12: Andrew Davidson, President, Andrew Davidson & Co., Inc.
Chapter 13: Andrew B. Weisman, Managing Director, Merrill Lynch.
Chapter 14: Clifford S. Asness, Managing and Founding Principal, AQR Capital Management, LLC.
Chapter 15: Stephen Kealhofer, Managing Partner, Diversified Credit Investments.
Chapter 16: Julian Shaw, Head Risk Management & Quantitative Research, Permal Group.
Chapter 17: Steve Allen, Deputy Director, Masters Program in Mathematics in Finance, Courant Institute of Mathematical Sciences, New York University.
Chapter 18: Mark Kritzman, President and CEO, Windham Capital Management, LLC.
Chapter 19: Bruce I. Jacobs and Kenneth N.Levy, Principals, Jacobs Levy Equity Management.
Chapter 20: Tanya Styblo Beder, Chairman, SBCC.
Chapter 21: Allan Malz, Head of Risk Management, Clinton Group.
Chapter 22: Peter Muller, Senior Advisor, Morgan Stanley.
Chapter 23: Andrew J. Sterge, President, AJ Sterge (a division of Magnetar Financial, LLC).
Chapter 24: John F. (Jack) Marshall, Ph.D., Senior Principal of Marshall, Tucker & Associates, LLC and Vice Chairman of the International Securities Exchange.
Notes.
Bibliography.
About the Contributors.
About the Authors.
Index.
Excerpts
David Leinweber, Leinweber & Co:
...It is remarkably easy to fool yourself. Once as a demonstration, we set our machinery loos to find the best predictor of the year-end close for the S&P 500. We avoided any financial indicators, but used only data the UN compiled profiling 145 member nations. There were thousands of annual times series for each country.
Which of all these series had the strongest correlation with U.S. stocks? Butter production in Bangladesh, with a correlation of 75 percent! Getting into the spirit, we tossed in cheese, and brought t up to 95 percent. (...) so added sheep population to the mix and take it up to 99 percent, in sample, over 10 years. Adding random data to a regression does tht. The out-of-sample predictions are less than worthless, often negative.
Ronald N. Kahn, Global Head of Advanced Equity Strategies, Barclays Global Investors.
With the importance of the information ratio in mind, Richard Grinold's "Fundamental Law of Active Management" shows that information ratios depend on the product of skill and breadth. Skill measures the investor's edge in every investment decisions. For example, how often do their stock picks outperform the benchmark? Breadth measures the number of available independent decisions.
Gregg E. Berman, Vice Chairman, RiskMetrics Group:
Eventually, I cam to some solid conclusions about trend following and convinced myself these strategies would no longer produce the same level of profits in the years ahead than they had in the years behind. I also found that I had lesss of a stomach for the huge ups-and-downs of trading then I had previously believed.
The more I wracked my brain, the more I realized I liked the detailed analytical parts of my job much more than the trading parts. It seemed to me that making money in the markets involved a much higher percentage of luck than was compatible with my academic persona.
I needed something where working harder and becoming smarter proved to be an advantage rather than just a distraction.
Mark Anson, CEO, Hermes Pensions Management Ltd.; CEO, British Telecommunications Pension Scheme:
(...) concerned with understanding the empirical relationship between economic variables. This is why I became a quant. I want to be able to ask and asnwer the questions why and how.
Andrew B. Weisman, Managing Director, Merrill Lynch:
The basic performance enhancement tool kit consists of: (1) smoothing; (2) selling volatility (i.e., taking premium while assuming the potentially significant risk of a low probability event); and (3) doubling up when your're wronf.
Smoothing; the big honking loss associated with having to sell a boatload of toxic securities in a short period of time when all your erstwhile buddies know what you're trying to do.
This is one example of just why quantitative financial research is so darn difficult; it involves rational (or at least thinking) participants who are not typically bound by the persistent laws of the physical world.
When overall exposure "loads" in a negatively correlated fashion with profitatbility, you've found what you're trying to avoid.
I learned (...) the need to cast a skeptical eye on any quantitative technique that had the potential to produce a flag pole solution - namely, a solution that was too finely calibrated to function out of sample. In my experience the two primary culprits were mean variance optimization (MVO), and value at risk (VaR).
My VaR is more than it was a week ago, less than it was three weeks ago, but what "it" is, is not truly knowable.
Senior Wall Street management has finally come to understand that investing is an intellectual arms race.
Stephen Kealhofer, Managing Partner, Diversified Credit Investments:
Finance is a beautiful field. First, it touches everything, so it has a license to explore the world. Second, there is more data in finance than any field I can think of. Of the many great things about markets is that they generate large amounts of high quality data about the actions of people. Third, the path from data analysis to the implementation of business ideas is incredibly fast. In biotechnology, it is measured in decades; in finance we do it in months or even weeks. Fourth, if you can deduce something useful, you get paid.
Julian Shaw, Head Risk Management & Quantitative Research, Permal Group:
Usually you can find a problem with the same mathematical form, often in an apparently unrelated discipline. The art of the quant is to find appropriate tools and bolt them together to create an effective soluton to the problem at hand.
Although some hedge funds managers have talent, most do not; quantitative analysis combined with qualitative analysis shows that most superficially spectacular track records can be explained by a combination of risk exposures and luck.
Steve Allen, Deputy Director, Masters Program in Mathematics in Finance, Courant Institute of Mathematical Sciences, New York University:
The importance placed on making economic forecasts began to fade relative to the importance of understanding the risht relationships between instruments.
Mark Kritzman, President and CEO, Windham Capital Management, LLC:
The hierarchy of investment choice: Other approaches for sorting out the relative importance of asset allocation and security selection, suchas as Brinson, Hood, and Beebower (BHB) and Ibbotson and Kaplan focused on the realized returns of managed portfolios; consequently, these studies failed to disentangle investment behavior from investment opportunity.
My colleague, Sébastien Page, and I performed the analysis using bootstrap simulations of available returns and discovered that security selection was overwhelmingly more important than asset allocation. This outcome, which we did not anticipate, provoked considerable debate among academics and practitioners.
Bruce I. Jacobs and Kenneth N.Levy, Principals, Jacobs Levy Equity Management.
Our investment approach is based on a philosophy of market complexity. (...) Equity market returns are driven by complex combinations of company fundamentals, economic conditions, and behavioral finance.
Earnings estimate revisions and earnings surprises, by contrast, are more important for growth than for value stocks.
Once modeled, return-predictor relationships are likely to change over time. (...) Merely tilting a portfolio toward historical anomalies does not produce consistant performance. It takes ongoing research on new inefficiencies, new sources of data, and new statistical techniques to keep an investment approach in synch with evolving opportunities.
By providing a clearer picture of the precise relationships between stock price behavior, company fundamentals, and economic conditions, disentangling improves return predictability.
Our experiments (...) show that only a relatively small proportion of momentum investors can destabilize markets, overwhelming value investors.
Allan Malz, Head of Risk Management, Clinton Group:
In the nature of random things, the worst loss is always in the future.
John F. (Jack) Marshall, Ph.D., Senior Principal of Marshall, Tucker & Associates, LLC and Vice Chairman of the International Securities Exchange:
In other words, a futures contract is an exchange of promises that neither party intends to keep and both parties know it.
