Finance professors should easily recognize today's menu of engineered derivative products in the marketplace. These hyper-sophisticated devices and models, many of which were at ground zero of the recent financial meltdown, are pure translations of their graduates' academic instruction. Indeed, the recent failure of many of these complex financial products and sophisticated quantitative models is a very loud warning to the academy that graduate instruction in finance might need to change.
Today's graduate classroom in finance is far different from that of only a decade ago. Benjamin Graham's securities analysis has been replaced by differential equations, vector calculus, linear algebra, non-linear econometrics and other complex statistical methods. Other graduate programs go much further, requiring proficiency in sophisticated computer programming languages such as C++.
The market has certainly responded. After several cycles of hiring, the momentum for quantitative skills has increased not only within the offices of the vendors of investment products, but also more importantly within the ranks of their similarly educated clients.
Despite its absence in finance, a hot debate over the proper application of these complex methods has been raging for well over a century in the closely related academic discipline of economics. Indeed, arguments made by the old economists about the proper use of these methods might apply to the world of finance as we see it today — and for that reason, might be worth revisiting.
For example, more than 75 years ago, influential British economist John Maynard Keynes criticized the use of certain complex mathematical methods, saying they were “concoctions, as imprecise as the initial assumptions they rest on.” But he did not advocate the elimination of higher-order mathematics and quantitative methods from economics research. He simply urged that they be used with full understanding of real world limitations — the same limitations our finance students will face once they become decision-makers in the City of London or on Wall Street.
In 1948, noted economist Kenneth Boulding argued in the Journal of Political Economy for a more holistic approach to the study of economics. He stated, “Mathematics is only part of the foundations of economic analysis; its other foundations lie in philosophy, in the other social sciences, and even in art and literature where that essential but non-mathematical quality of critical judgment is developed.” In other words, a financial derivatives course should not only teach the "greeks' (i.e., option price sensitivities), but also the Greek philosophers! Mr. Boulding seems to suggest that our finance students should spend a considerable amount of time learning how to think and to reason, as well as how to compute.
More recently, the Commission on Graduate Education in Economics, stocked with academic luminaries such as Nobel Laureate Kenneth Arrow, Alan Blinder and Lawrence Summers, addressed complaints that “economics as taught in graduate school had become too divorced from real-world questions.” The COGEE's final report, published in 1991 in the Journal of Economic Literature, reflected the authors' concerns that students were graduating with a better understanding of mathematics than of an understanding of the fundamental questions in economics. COGEE commissioners worried that economics programs were at risk, as they said, to “teach the language of mathematics but not the logic of economics.”
The report lamented, “One member of the commission observed that bright students who have no difficulty following complex mathematical arguments nonetheless stumble over standard undergraduate microeconomic questions — such as when to cut down a tree.”
Similarly, we might ask why our finance graduates who ultimately achieved great career success leading Wall Street powerhouses such as Merrill Lynch did not understand that a 40:1 capital ratio, a level allowed by their complex risk models, could potentially lead to the total collapse of the company.
In her 1992 speech, Lynn Michaelis, chief economist of the Weyerhaeuser Co. and president of the National Association of Business Economists, admitted, “Unlike physics where relationships appear hard-wired, we are dealing with human beings and their institutions, which adapt and change over time.” Ms. Michaelis' arguments were a clear echo of Mr. Keynes' earlier pragmatism and directly apply to classroom instruction in finance today.
The critical question when teaching quantitative methods to our finance students is how to instruct them to deal with future error and uncertainty. Our graduates will undoubtedly produce numerous ex ante forecasts when constructing portfolios or managing risk for their clients and employers. But our employed students will quickly discover that the greatest threat to short-term success is not whether their forecasts will contain error, but how big that error will be. And then most importantly, what are the potential consequences of that error, regardless of its size.
Since we in academia are immune from real market consequences in our research, we often fail to fully appreciate how critical this latter question is to success. But the question of consequences is one the finance industry and participants in the global economy recently came to understand all too well.
Our graduates' forecast error, a function of a probability distribution, and computed by the likes of Ph.D.s working in hedge funds, is not the only source of imprecision. Our finance graduates will also face a future filled with an unknowable set of events that will impact results in unknowable quantities. Peter Bernstein, in his book “Against the Gods, The Remarkable Story of Risk,” addresses this uncertainty, stating that “surprise is endemic above all in the world of finance.”
Mr. Bernstein's book was published well before the recent financial collapse, but his arguments have considerable relevance for the teaching of quantitative models such as value-at-risk — a rigid algorithmic academic-based risk management tool that has now come under great criticism for its role in the financial crisis. Mr. Bernstein asks: “If these events were unpredictable, how can we expect the elaborate quantitative devices of risk management to predict them? How can we program into the computer concepts that we cannot program into ourselves, that are even beyond our imagination?”
Business school administrators and faculty have indeed responded to recent economic events and many have already implemented significant changes to their academic programs. Last year, Columbia University conducted a wholesale program review following the financial collapse. That school — along with the University of Chicago, Harvard Business School and many others — introduced new coursework and coverage in the area of crisis management, ethics and corporate governance. Unfortunately, revisions are not as apparent in the specialized quantitative finance curricula of the top U.S. programs. Online curriculum guides for many of these programs still read very much as they did in 2007, stuck in time as if nothing has happened.
The COGEE authors, each possessing a highly quantitative academic background, worried that graduate programs in economics may be “turning out a generation with too many idiots savant, skilled in technique but innocent of real economic issues.”
Today, many of the top quantitative finance programs, such as the graduate curricula offered by Rutgers, New York University and Columbia University, are not actually taught by finance faculty within their respective schools of business. Classes are instead being directed and taught within the schools of math and science — a world away from any critical instruction on the behavioral aspects of management and markets.
Finance and math professors are today graduating tomorrow's bankers, public pension directors and securities regulators. The finance academy should carefully consider whether we, too, are turning out graduates overly skilled in quantitative technique, but innocent of the fundamental realities of financial markets.
Kenneth E. Scislaw is visiting assistant professor of finance, Drury University, Springfield, Mo.