B. Ross Barmish received the Bachelor's degree in Electrical Engineering from McGill University in 1971. In 1972 and 1975 respectively, he received the M.S. and Ph.D. degrees, both in Electrical Engineering, from Cornell University. From 1975 to 1978, he served as Assistant Professor of Engineering and Applied Science at Yale University. From 1978 to 1984, he was as an Associate Professor of Electrical Engineering at the University of Rochester and in 1984, he joined the University of Wisconsin, Madison, where he is currently Professor of Electrical and Computer Engineering. From 2001 to 2003, he was with the Department of Electrical Engineering and Computer Science at Case Western Reserve University, where he served as Department Chair while holding the endowed Nord Professorship. Over the years, he has been involved in a number of IEEE Control Systems Society activities such as associate editorships, conference chairmanships, the Board of Governors and prize paper committees. He has also served as a consultant for a number of companies and is the author of the textbook New Tools for Robustness of Linear Systems, Macmillan, 1994. Professor Barmish is a Fellow of both the IEEE and IFAC for his contributions to the theory of robustness of dynamical systems. He received the Best Paper Award for Journal Publication in Automatica, covering a three-year period, on two consecutive occasions from the International Federation of Automatic Control. He has also given a number of plenary lectures at major conferences. While his earlier work concentrated on robustness of dynamical systems, his current research, the topic of this Bode lecture, concentrates on building a bridge between feedback control theory and trading in complex financial markets.
My answer is "yes." In this lecture, I will make the case that there are some important open problems in finance which are ideally suited for researchers who are well versed in control theory. To this end, I will begin the presentation by quickly explaining what is meant by the notion of "technical analysis" in the stock market. Then I will address, from a control-theoretic point of view, a longstanding conundrum in finance: Why is it that so many asset managers, hedge funds and individual investors trade stock using technical analysis techniques despite the existence of a significant body of literature claiming that such methods are of questionable worth with little or no theoretical rationale? In fact, detractors describe such stock trading methods as "voodoo" and an "anathema to the academic world." To date, in the finance literature, the case for "efficacy" of such stock-trading strategies is based on statistics and empirical back-testing using historical data. With these issues providing the backdrop, my main objective in this lecture is to describe a new theoretical framework for stock trading - based on technical analysis and involving some simple ideas from robust and adaptive control. In contrast to the finance literature, where conclusions are drawn based on statistical evidence from the past, our control-theoretic point of view leads to robust certification theorems describing various aspects of performance. To illustrate how such a formal theory can be developed, I will describe results obtained to date on trend following, one of the most well-known technical analysis strategies in use. Finally, it should be noted that the main point of this talk is not to demonstrate that control-theoretic considerations lead to new "market beating" algorithms. It is to argue that strategies which have heretofore been analyzed via statistical processing of empirical data can actually be studied in a formal theoretical framework.