Financial Engineering

Advisory Prerequisites: MATH 217, 417, or 419. (3 credits)

Formulation of problems from the private and public sectors using the mathematical model of linear programming. Development of the simplex algorithm; duality theory and economic interpretations. Post-optimality (sensitivity) analysis application and interpretations. Introduction to transportation and assignment problems; special purpose algorithms and advanced computational techniques. Students have opportunities to formulate and solve models developed from more complex case studies and to use various computer programs.

Prerequisites: IOE 316 or Stats 310. (3 credits) 

Introduction to non-measure theoretic stochastic processes. Poisson processes, renewal processes, and discrete-time Markov chains. Applications in queueing systems, reliability, and inventory control.

Prerequisites: IOE 201, IOE 310, IOE 366. (3 credits)

The main objectives of the course are first, to provide the students with a thorough understanding of the theory of pricing derivatives in the absence of arbitrage, and second, to develop the mathematical and numerical tools necessary to calculate derivative security prices. We begin by exploring financial markets and the implications of the absence of static arbitrage. We study, for instance, forward and futures contracts. We proceed to develop the implications of no arbitrage in dynamic trading models: the binomial and Black-Scholes models. The theory is applied to hedging and risk management.

Advisory Prerequisites: IOE master’s student or permission of instructor. (1 credit)

Seminars presented by academic speakers and industry leaders to describe contemporary applications of industrial and operations engineering models and techniques to master’s students in IOE. The focus is on applications but research challenges are addressed as needed. Many speakers also address potential career opportunities for MS students in IOE.