Can Control Science Bring New Insights to Stock Trading Research?

Abstract

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.