Replies by Steve Shreve.
1) The MBA has traditionally been the preferred "fishing pond" for investment banks and other financial institutions looking for young, fresh, ambitious talent. With the arrival in force of specialist finance and quantitative finance programs in the past few years, do you think that the status quo has been drastically altered?
Yes, although the sea change began before the creation of quantitative finance programs. The Carnegie Mellon Master's program in Computational Finance was among the first, beginning in 1994. D.E. Shaw and the hedge fund Medallion, which spawned Renaissance Technologies, both began in 1988. By the time we started our program, investment banks, hedge funds, and even some energy firms were seeking to build quant groups. Of course, the proliferation of professional master's programs in quantitative finance has made it possible for this trend to accelerate, and it surely has. Now major banks are seeking highly quantitative talent even for trading positions.
2) Based on your experience, are hiring managers in charge of finding risk management talent now actively seeking graduates with specialty finance degrees? Do aspiring risk managers who graduate with a degree in, say, general finance or computational finance have an edge over students who graduate with an MBA? Why or why not?
My experience has been that hiring managers for financial risk management groups in banks and other financial institutions seek quantitative talent. This does not preclude MBA students, provided they have an engineering or science undergraduate degree.
Especially in model validation groups within risk management, a quantitative background, perhaps even at the Ph.D. level, is essential. There is also the whole field of enterprise risk management, which covers legal risk, operational risk, and other less quantifiable risks. I do not have direct experience with the hiring managers for these areas, but my general impression is that the MBA background is more appropriate for these than is a computational finance background.
3) Some schools have chosen to go the "quant route" big time. Why has/hasn't your university chosen that path. Do you expect to see more quantitative finance programs emerge in the near future. Or is quant finance education an unsustainable bubble?
Carnegie Mellon has chosen the "quant route" because the demand was present and we had the ability to fill it. We have a spirit of cooperation among the disciplines needed for quantitative finance, and we have faculty in each of those disciplines willing to step up to the plate. It is difficult for me to predict whether other universities will continue to develop quant finance programs, but I am confident that we are not seeing a "bubble." Our program continued to grow and have very high placement rates even during the difficult years experienced by financial services firms from 2000-2003.
After the collapse of Enron and WorldCom, the demand for quants in the United States increased as firms built staffs to comply with the requirements of the Sarbanes-Oxley Act. The current credit crisis may again increase demand. The models we have for credit markets have long been known to be inadequate, and going forward, those who trade on these models will be required to understand them and their limitations in a way that only quantitatively trained people can.
4) How does your program train financial risk managers? What specific parts of your curriculum provide direct value to risk managers? And how large of a demand is there in the risk management community for students who graduate from your program?
Our program contains a serious treatment of stochastic calculus, simulation, regression, times series, and statistical inference.
Students learn how to build and use models to hedge risk and the assumptions behind the models so that they are aware of their shortcomings. They learn to simulate market prices under normal conditions and also to simulate rare events. In the mid 1990s many of our students took risk management positions. In recent years they have tended more toward "front office" positions such as structuring, strategy, analytics, trading and trading support and toward hedge funds. I believe this change is mostly a result of student preference, not because our students are less desirable to risk managers.
5) Of all the business-related disciplines, finance is probably the one that has experienced the deepest theoretical and mathematical "offensive." Do you think that financial education has become too abstract? How much weight do you think should be assigned to technical, as opposed to practical, aspects? And how much weight would you assign to real-life experience?
I am a mathematician, so it is difficult for me to suppress my bias here. There are topics that are best taught at universities because they require a systematic approach and time to assimilate.
One should learn at universities those topics that are important for a career, have lasting value, and cannot be easily learned on the job. Mathematics is one of these.
However, good applied mathematics requires a person to know mathematics well and to know the application area well. Derivative security pricing and trading, quantitative asset management, financial risk management all require an understanding of markets and the models that are built to describe them. Some programs focus more on the models, and others more on the markets. I believe there should be a balance. At Carnegie Mellon we listen to our alumni, our advisory board, and recruiters in order to maintain that balance. We invite practitioners into our program via a seminar series and in some cases to help teach courses.
If "real-life experience" means the ability to take knocks and keep going, to lead a team even if it contains difficult members, and to communicate effectively, then this is an important aspect of success in almost every endeavor. During the admissions process we look hard for applicants who have these skills.
6) Is a more quantitative education a better fit in the risk management community than an "intuitive and practical" education? What's more relevant for risk managers, for example, how to calculate VaR or how to understand markets?
Blindly calculating VaR is a formula for disaster. Knowing how to hedge, the extent to trust the hedges, and how to control exposure are more important skills. These, of course, require a mixture of "intuitive and practical" knowledge and quantitative skills.
7) There are five super-hot areas in real-world finance at the moment: M&A, hedge funds, private equity, credit derivatives and sovereign wealth management. Would you say that your program helps prepare for all five types of careers? In your view, which is better: a program that provides a general overview of each of the five or one that provides very thorough training in just one or two? Why?
Life can change quickly. The fact that the premise of the question is so suspect only a month after it was posed shows the importance of having fundamental skills that are not closely tied to any particular "super-hot" area. To do otherwise is to be a young kid playing soccer -- always chasing the ball and never anticipating it. Some of these fundamental skills are the ability to think rigorously, the ability to take a problem apart into its constituent parts and analyze the pieces (including building mathematical models where appropriate), the ability to communicate and to listen. Of course, a professional degree program should also address the more specific aspects of a particular career. We like to think of ourselves as providing a broad education within the niche career of quantitative finance.
The five areas listed in the question cover such a spectrum that it is difficult to conceive of a program that does justice to all of them -- some are highly quantitative while others are relationship driven. A program that covers only one of the five areas would be rather narrow. A program that provides the base so that graduates can go into two or three of these areas is desirable.
8) Do you see any significant trends emerging in finance education over the next two years?
In recent years the demand for quantitatively trained finance professionals has outstripped supply, and many mathematical science departments have moved to meet this demand. If we are entering a period of retrenchment in the finance industry, employers will be able to insist that the people they hire have the polish of an MBA and the skill set of an engineer. This will encourage MBA programs to create quantitative tracks within their schools, perhaps by partnering with other departments as we have done at Carnegie Mellon, because graduates of such tracks will be in demand even when narrowly educated quants and broadly educated non-quantitative MBAs are not. However, I expect it will take longer than two years for this scenario to play out.