The first half records Dr. Derman’s depressing and futile search for a career in academic physics (he earned his doctorate in 1973 as a glut of newly minted baby-boom physicists were seeking a shrinking, post–space race number of professorships). Some readers may be tempted to skip directly to his arrival on Wall Street in 1985, but they would miss a lot. His account of his early intellectual journeys in physics informs his later descriptions of the difficulties of solving problems in finance.
Although he is modest about his own accomplishments, Dr. Derman made significant contributions to options pricing theory during his Wall Street years, most of which were spent at Goldman Sachs, sometimes working with Fischer Black. Together with Dr. Black and Bill Toy, another Goldman quant, he created a model that extended the original Black–Scholes formula to the bond market. Dr. Derman is remarkably good at explaining the complexities of securities, judiciously using charts and a bit of math to illuminate theory. But his special gift is his ability to communicate complicated ideas in plain English. Why are bond options harder to price than stock options? He writes:
Bonds are connected to each other. The future behaviors of a five-year bond and a three-year bond are not independent, but overlapping: Two years from now, the five-year bond will be a three-year bond, so you cannot model one bond’s future without implicitly modeling another. In fact, it is impossible to model one bond without modeling all of them.
The Black–Derman–Toy model was both an intellectual and a commercial success, and was immediately put to use by traders. While admitting its imperfections, Dr. Derman notes, with satisfaction, that “it continues to be used even after superior but more complex models have arrived on the scene.”
My Life as a Quant takes us through the 1990s. (Dr. Derman left Goldman Sachs in 2002, took a year off to write his book, and returned, full circle, to academia, as a professor and director of the program in financial engineering at Columbia University.) But the quest to better understand the relationships between risk and return continues, as both finance professors and Wall Street quants endlessly refine their models and techniques to embrace new insights.
How Irrationality Counts
The newest vein of academic research, which has emerged over the past decade, is behavioral finance, the study of how psychology affects investors and the financial environment. Its central argument is that investors do not behave rationally. As Hersh Shefrin puts it in his useful overview of the field, Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing, “Errors and bias cut across the entire financial landscape, affecting individual investors, institutional investors, analysts, strategists, brokers, portfolio managers, options traders, currency traders, futures traders, plan sponsors, financial executives, and financial commentators in the media.”
Behavioral finance received a huge boost from the heady rise and grim denouement of the stock market bubble of the late 1990s. Here was a challenge to the assumptions of the efficient markets school that was obvious to everyone — indeed, that had a serious and tangible financial impact on millions of hapless workers and investors. Whatever else the markets were doing as the Nasdaq index rose to its peak of 5132 in March 2000 (in early 2006 it was still well below half that level), they were not behaving rationally.
Wall Street firms are incorporating insights from the behavioral finance field into their trading strategies and into the investment products they offer, and others are exploring its implications for corporate strategy (see “Love Your 'Dogs,'” by Harry Quarls, Thomas Pernsteiner, and Kasturi Rangan). Although behavioral finance hasn’t yet produced a paradigm-shifting new practical tool for financial engineering in the league of the capital asset pricing model or the Black–Scholes formula, it’s a safe bet that the battalions of researchers at work in the new field will discover further ways to refine quantitative finance in the future.