Econometrics -- Economics (ECON) 240A [5 units]
Description: Basic preparation for the Ph.D. program including probability and statistical theory and the classical linear regression model.
Financial Engineering Systems I -- Industrial Engineering (IND ENG) 222 [3 units]
Description: Introductory graduate level course, focusing on applications of operations research techniques, e.g., probability, statistics, and optimization, to financial engineering. The course starts with a quick review of 221, including no-arbitrage theory, complete market, risk-neutral pricing, and hedging in discrete model, as well as basic probability and statistical tools. It then covers Brownian motion, martingales, and Ito's calculus, and deals with risk-neutral pricing in continuous time models. Standard topics include Girsanov transformation, martingale representation theorem, Feyman-Kac formula, and American and exotic option pricings. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation.
Applied Stochastic Process I -- Industrial Engineering (IND ENG) 263A [4 units]
Description: Conditional Expectation. Poisson and renewal processes. Renewal reward processes with application to inventory, congestion, and replacement models. Discrete and continuous time Markov chains; with applications to various stochastic systems--such as exponential queueing systems, inventory models and reliability systems.
Game Theory in the Social Sciences -- Economics (ECON) C110 [4 units]
Description: A non-technical introduction to game theory. Basic principle, and models of interaction among players, with a strong emphasis on applications to political science, economics, and other social sciences. Also listed as Political Science C135.
Last semester as a Math/Econ major. I'm thinking of just replacing the game theory class with the honors thesis.