Distinguished Lecture: From Simple Information-Theoretic Ideas on Gambling to Algorithmic Stock Trading

Abstract: In this talk, I will provide an introduction to some of my work on algorithmic trading in the stock market. No expertise in finance will be needed to follow the exposition. To keep things simple, in the first part of this talk, I will begin with the analysis of a simple coin-flipping game involving a biased coin with probability of heads p > 1/2 which is known by the bettor. To find an optimal betting scheme, we work with the Expected Logarithmic Growth Criterion, introduced in the mid-1950s by John Kelly and Claude Shannon at Bell Labs, in the context of information theory, and the subject of a voluminous body of literature in the decades to follow. The second part of this talk is motivated by the following fact: In volatile financial markets, the stochastic process for stock returns is not easily modelled and can be highly non-stationary. With this consideration in mind, we revisit the coin-flipping problem and no longer assume that the probability of heads p is known. This leads to analysis of a betting strategy called Simultaneous Heads-Tails. This scheme involves a simple feedback on the gambler’s time-varying account value. Finally, I will describe some of the issues, both theoretical and practical, which arise when we translate the ideas about coin-flipping into the trading of stock. This includes topics such as back-testing with historical data and mechanics associated with the trader’s interactions with the broker and the stock exchange.

Biography: In early 2019, B. Ross Barmish joined Boston University as Research Professor in the Department of Electrical and Computer Engineering. Prior to joining BU, he held faculty positions in engineering at the University of Wisconsin, the University of Rochester and Yale University. From 2001-2003, he served as Chair of the EECS Department at Case Western Reserve while holding the Nord Endowed Professorship. He received his Bachelor’s degree in EE from McGill University and the M.S. and Ph.D. degrees, also in EE, from Cornell University.

Throughout his career, he has served the IEEE Control Systems Society in many capacities and has been a consultant for a number of companies. Professor Barmish is the author of the textbook “New Tools for Robustness of Linear Systems” and is a Fellow of both the IEEE and IFAC for his contributions to robust control. He received two Best Journal Publication awards, each covering a three-year period, from the International Federation of Automatic Control and has given many keynotes and plenary lectures at major conferences. In 2013, he received the IEEE Control Systems Society Bode Prize.

While his earlier work concentrated on robustness of dynamical systems, his current university research involves building a bridge between feedback control theory and trading in complex financial markets. In addition to this academic pursuit, in his capacity as CEO of Robust Trading Solutions, his work involves transition of stock-trading algorithms from theory to practice and government sponsored research on the NASDAQ Limit Order Book.


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The School of Electrical Engineering and Computer Science was created in the spring of 2015 to allow greater access to courses offered by both departments for undergraduate and graduate students in exciting collaborative research in fields.

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