I’m very pleased and very honored to be able to introduce Dr Oldrich Vasicek here today on his induction into the Derivatives Hall of Fame. Ever since I first started to learn about financial theory fifteen or so years ago, I’ve admired Dr Vasicek from a distance, for several reasons. The most trivial one is that my wife, like him, was raised in what was then Czechoslovakia, leaving there in 1968 for this country. Less trivially, I was inspired by the way he managed to combine the highest academic standards with real business. But there are deeper reasons too.

Everybody these days likes to talk about Financial Engineering. It’s a fairly recent term, certainly post-dating much of the work for which Vasicek is famous, and it’s not a term I’m over-enthusiastic about. I think that if I had to describe Vasicek, or indeed Mark Rubinstein, to someone outside the field, I would characterize both of them not as financial engineers, but rather as financial scientists. Let me explain what I mean.

Engineering is practical, concerned with construction, be it of machines, buildings, financial instruments or risk systems. It can rest on a bed of science, or it can proceed in parallel in a more pragmatic way. Financial science goes farther: it’s the development of causal, dynamical theories for the valuation of securities; it’s theories that progress from (1) noting the simple dependency of variables through (2) structural relations between these variables, to (3) mechanism, dynamics and causality. Science means there are assumptions, deductive rules, and a discipline for applying them. Statistical arbitrage, regressions, and other forms of what I like to call financial pattern-seeking are concerned more with relationships, less with dynamics, and, useful though they may be, fall short of real science. Dynamics and causality are the hallmarks of Vasicek’s work in derivatives.

Joe Kolman sent me Vasicek’s Curriculum Vitae – he had the Latin phrase we used for resumes in the old days printed at the top of it. He published his first paper, on some geometric problems, while still in high school. He graduated with an M.S. in Mathematics from Czech Technical University in Prague in 1964, and then worked as a scientist at the Czechoslovak Academy of Science and the Technical-Economic Institute in Prague, while working on his Ph.D., which he received from Charles University in Prague in 1968, in Probability Theory. Then he moved to the U.S., working for more than ten years at Wells Fargo in San Francisco during what must have been the wonderful salad days of financial economics, and then in the fixed-income analytics area at Gifford Fong Associates. Starting in 1983, as usual well ahead of his time, he headed in the direction of credit, co-founding the Diversified Corporate Finance Co. In 1989, going farther again, he co-founded the KMV Corporation with Kealhofer and McQuown. Also, during the 1970’s, he held academic appointments at Rochester & Berkeley.

Vasicek became famous for his 1977 paper called An Equilibrium Characterization of The Term Structure, probably the first paper to apply the insights of arbitrage-free options theory, hedging and equilibrium to bonds and the yield curve. Lately, eloquent physicists have started talking rather dramatically about string theory, which is a difficult and still unsolved attempt at a unified theory of everything, as a little bit of 21st century physics that accidentally fell into the 20th century.” Vasicek’s model was a building brick of 1990’s financial theory that somehow fell into the 1970s. Everyone who now works on fixed-income models is mostly expanding on Vasicek’s original approach. I also heard him give a fascinating talk, about ten years ago, on Wall Street, on a model for valuing the delivery option in fixed-income futures.

But financial progress isn’t just made with theory. I sometimes think that the history of successful models in financial theory is described by one of Blake’s proverbs, one I always liked:

“If a fool would persist in his folly, he would become wise.”

Who in his right mind, fifty years ago, would have predicted that traders would discuss securities based on their estimate of the future sum of the squared deviations of a return from its mean – its volatility? Black and Scholes struggled to get their ambitious folly published, and now not only MBA students, but even traders, learn stochastic calculus.

I’m inspired by Vasicek’s record because it illustrates that the right kind of persistence pays: taking a simple intuitive model very seriously makes excellent sense. Vasicek has been persistently wise, first in applying equilibrium ideas to interest rates, and second in not giving up on the idea of regarding a stock as an option on the assets of the firm, and then milking that courageous picture of market prices for all it’s worth to predict the market’s perception of default probabilities.

I took a look at KMV’s web page. It emphasizes that their model is structural, is “a causal model – not a statistical estimation,” and that its “predictive power reflects that equity prices contain substantial information about the value and volatility of a firm’s business.” Finally, they “focus on models with as few parameters as possible,” and “favor economic intuition over mathematics.”

To me, this is just the mix of science and hubris that has made derivatives theory the most advanced and yet practical part of finance. It’s an honor to congratulate Dr Vasicek on his award, recognizing both his scientific skills and his character that allowed him to never give up in the quest to extract human intuition from market prices.