Graduate
Investment Theory (FIN 5320)
This course covers the theory of risk and return in capital markets. Topics covered include the CAPM and factor models of asset pricing, measures of mutual fund performance evaluation, interest rates and fixed income securities.
Topics in Quantitative Finance (FIN 5018)
The main objective of this course is to familiarize students with the current cutting-edge techniques implemented by the quantitative finance industry. The contents of this course can vary from year to year. Topics may include risk management, statistical arbitrage, and derivative pricing and hedging. Some practical projects may be used for implementation of these techniques.
Stochastic Foundations for Finance (FIN 5380)
This is a foundations course, which is designed as a prerequisite to FIN 5390, Mathematical Finance. It is therefore mainly designed for students in the Masters in Finance program who aim at quantitative positions in investment banks, hedge funds and consulting firms. While financial examples will be given, the primary focus will be on stochastic process and stochastic calculus theory. Students interested in applications of the theory are expected to take follow-on courses. Topics to be covered include: general probability theory; Brownian motion and diffusion processes; martingales; stochastic calculus including Ito’s lemma; and jump processes.
Derivative Securities (FIN 5241)
Covers Black-Scholes option pricing model. Provides an in-depth analysis of valuation and trading strategies for options and other derivative securities. Potential applications could include hedging, swaps, index arbitrage, corporate decision making, and financial market innovation.
CFAR Practicum (FIN 5019)
The CFAR Practicum provides consulting project opportunities for WAM, Fintech, Quant, and MBA Finance students. Students work in teams to complete a project with a company, developing sophistication in the transfer of cutting-edge financial techniques putting the academic environment into practice. Faculty advisors help teams manage the relationships with clients and make the bridge between the academic tools the students have learned and the practical projects provided by the companies. Students’ grades are based on deliverables throughout the semester including the final presentation at the conclusion of the project.
Data Analysis For Investments (FIN 8533)
The objective is to obtain an in-depth understanding of some of the major empirical issues in investments and to gain the implementation skills. Based on recent advances, students are required to learn the facts, theories and the associated statistical tools to analyze financial data with Python, and with some optional tutorial and codes in R and Matlab. The topics include portfolio optimization, factor models, factor investing, Bayesian and shrinkage estimations, principal analysis, predictability, big data tools, asset allocation, stock screening, performance evaluation, anomalies, limits to arbitrage, behavioral finance, and Black-Litterman model.
Options and Futures (FIN 5240)
Introduces the derivative markets with a focus on options and futures. Covers forward and futures pricing, and the use of futures contracts to hedge risk. Discusses option valuation primarily through binomial models.
Undergraduate
Options, Futures and Derivative Securities (FIN 451)
This course examines the theory and practical application of derivative securities such as futures, options and swaps. Central to the theory of derivative security pricing is arbitrage and payoff replication. In practice, derivative securities provide a principal route to manage and, in particular, hedge financial risk. Futures, options and swaps on different types of underlying assets are examined with emphasis on pricing and application.