Course work forms the core of the program, and occupies the majority of students' efforts. Each course involves 13 weeks of
lectures, with associated written assignments, projects, tests and a final exam. Some courses include intensive use of scientific
computation and financial databases. M-Phimac students will take the following 7 master's level courses, providing a range of
expertise from highly mathematical foundations to topical business applications.
|MATH 771: Mathematics of Finance
Stochastic calculus, martingales and arbitrage, Black-Scholes
equation and pricing derivative securities, fundamental
theorems of asset pricing, models of equity and fixed
income markets, exotic options.
|MATH 776: Financial Markets
Overview of equity, fixed income and FX markets; summary
of discrete and continuous time financial modeling; pricing
of vanilla and exotic derivatives; discussion of volatility;
market risk, VaR, CAPM models; introduction to credit risk;
|MATH 772: Topics in Financial Mathematics
Stylized facts from financial time series; GARCH models;
stochastic volatility models; markets with jumps; Levy
processes; implications for pricing, hedging and risk
|MATH 774: The Mathematics of Credit Risk
Default events and stopping times; bonds and rates; credit
spreads and corporate bond prices; intensity based models;
credit rating models, firm value models; default correlation;
credit derivatives; calibration; basket credit products;
collateralized debt obligations.
|MATH 775: Portfolio Theory and Incomplete Markets
The continuous time portfolio problem; portfolio problems
with constraints, portfolio optimization in the presence of
transaction costs; risk measures; optimal cash management
in equity index tracking with transaction costs.
|MATH 790: Major Research Project
Completion of a project of industrial interest. Students will work
together with a mentor from a financial institution, or alternatively,
may complete the project while working as an intern or while
beginning work full time in the financial industry. Students deliver
a paper and an oral presentation at the end of August to complete their
A course in statistical methods for use in practice. Topics may
include central concepts and methods of statistical inference,
sampling distributions, point and interval estimation, and
testing of statistical hypotheses.