The lectures will cover the theory of relative entropy in statistics and information theory and its applications to theoretical and applied Finance.
The course is divided into 3 parts:
The course is intended for graduate students in mathematics, computer science, economics or finance, and for Wall Street quantitative analysts who want to explore the use of entropy, stochastic control and optimization techniques for calibrating asset models (for options, interest rates, credit?). A strong level of mathematical proficiency is assumed, as well as knowledge of asset pricing theory (e.g. Mathematics of Finance I or II).
Grades will be assigned by completing three take-home assignments, involving theoretical questions and computer programming.
The material will be drawn from Cover and Thomas: Elements of Information Theory and from journal papers. Names before the title of a lecture indicate the primary bibliographical source. When there are no names, the material will be drawn from my personal notes and I will give additional references in class.