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The Financial Engineering Program provides a flexible curriculum. Thirty-two units are needed to complete the degree. Twenty-four units are required courses. Eight units are elective courses. Recommended electives are offered every year during the semester listed. Other electives are not offered during a fixed semester; they are listed at the end of this curriculum section.
Fall Semester
Required Courses
Methods of Applied Probability and Statistics
The goal of this course is to study the fundamental concepts in the theory of statistical inference. Students will learn how to construct point and interval estimators and test statistical hypotheses based on data. Students will also learn the concepts of sufficiency and completeness as they relate to forming optimal point estimators, and how to apply the Neyman-Pearson theory to find optimal hypothesis tests.
Corporate Finance
This course develops understanding of financial decision making—including investment decisions, financing decisions, and their interaction—and examines the underlying framework of corporate finance, including valuation, market efficiency, portfolio theory, agency costs, and information costs.
Time Series Data Analysis
This course studies standard methods in handling time series data. These include stationary and non-stationary processes, seasonal models, univariate ARIMA and GARCH models. Some multivariate models along with state-space models and Kalman filter will also be discussed.
Stochastic Processes
This first part of the course covers Markov processes: Markov chains and pure jump processes. Ergodic theory and martingales are analyzed. The second part of the course covers second order processes such as Brownian motion. Stochastic integration and stochastic calculus (Ito’s lemma) are covered. Applications are given to queueing systems and default risk modeling.
Spring Semester
Required Courses
Mathematical Finance: Fixed Income and Derivatives
This course starts by describing financial derivatives in the following markets: equities, fixed income, credit, commodities, currency. Emphasis is then on the pricing of these securities by formulae or numerical techniques (Monte Carlo, trees, finite differences). We analyze the following models: Black-Scholes, stochastic volatility, Vasicek, SOFR and others. Stochastic calculus is used extensively. Real options are also discussed.
Quantitative Risk Management
This course focuses on developing tools to quantify and manage the different sources of risk in financial markets. In particular, we will develop tools to forecast volatility, calculate different measures of risk such as Value-at-Risk and Expected Shortfall by Monte Carlo (with or without copulae) or other methods, such as quadratic VaR. We will also study coherent measures of risk, risk aggregation, and capital allocation. Special attention will be given to credit risk: pricing risky bonds, counterparty risk, credit default swaps, securitization, and consumer credit risk. Other types of risk impacting financial institutions, such as model risk, operational risk, and liquidity risk, will also be covered. Topics will vary according to current market needs and may include ESG, climate, and cryptocurrency derivatives.
Recommended Elective Courses
Asset Management Practicum
Theories of asset management are presented via textbook and other readings, lectures, case studies, and student and guest speaker presentations. Students will be responsible for inviting some of the guest speakers with consultation by the instructor. Asset management firms establish and review investment policy, conduct investment research, determine strategies to be implemented, select securities, enter and track orders, measure and report performance, and manage client relations. We will study all these activities in the course.
Machine Learning for Asset Pricing and Management
This course covers basic optimization, machine learning, asset pricing and portfolio theory. Various types of investments such as stocks and bonds are described at the MBA level. Topics include mean-variance, mean-variance with learning (Black-Literman), strategic asset allocation, linear factor models, linear programming, PCA, clustering, and deep learning for asset pricing and management.
Statistical Learning
This course teaches statisticians and financial engineering practitioners cutting-edge statistical learning techniques to deal with vast and complex data in fields ranging from biology and finance to marketing and astrophysics.
Other Electives
The following courses may be offered in different semesters each year. Depending on their availability, they can be taken as electives:
- Quantum Computing and Applications
- Partial Differential Equations
- Math Clinic (two-semester sequence)
- Linear Statistical Models
- Discrete Mathematical Modeling
- Optimization
- Mathematics of Machine Learning
- Advanced Big Data Analysis
- Computational Statistics
- Financial Strategy & Valuation (Drucker)
- Selected Topics in Finance: Fixed Income (Drucker)
- Investments (Claremont McKenna College)
Accelerated Degree Option
Undergraduate students at the Claremont Colleges (Pomona, Scripps, Claremont McKenna, Harvey Mudd, Pitzer) can obtain a graduate degree on an accelerated track through the Claremont Graduate Scholars Program, working toward the master’s requirements simultaneously with the completion of an undergraduate degree. Up to 16 units of transferable credit can be earned upon admission to one of our master’s degree programs. Students are eligible for a minimum fellowship award of $6,500 per semester at CGU, based on 12 units of enrollment. Apply Here
Recent alumni of the Claremont Colleges (Pomona, Scripps, Claremont McKenna, Harvey Mudd, Pitzer) can obtain a graduate degree on an accelerated track through the Claremont Graduate Scholars Program. For alumni who have graduated within the past five years, up to 12 units of transferable credit can be earned upon admission to one of our master’s degree programs. See program-specific details for restrictions on applicable coursework. Students are eligible for a minimum fellowship award of $6,500 per semester at CGU, based on 12 units of enrollment. Apply Here
