The hallmark of the Master of Science in Financial Engineering (MSFE) is the close integration of mathematics and finance with the most recent computational developments. Our MSFE was the first to be established in California, and has long offered a strong curriculum in the foundational skills that will make you successful in industry. Beyond these skills, we embrace the fundamental changes that machine learning is bringing to the modern world.

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The MSFE program provides you with the expertise to create and evaluate complex financial products to help you become a strategic leader in the field. You will draw on tools from applied math, statistics, and financial and economic theory which you will convert into (i) software programs in the most modern programming languages and (ii) successful decision-making. Our program ranks among the top financial engineering programs nationally and gives our graduates excellent preparation for careers in portfolio management and risk management in various financial services institutions (banking, hedge funds, and financial technology companies).

The Claremont Colleges are proud to offer small class sizes. The MSFE program embodies this principle. We believe that students learn better with personalized teaching.


Program Highlights
  • Learn from research faculty and experienced practitioners with expertise in areas such as risk management, derivatives, asset management, and financial information systems among others.
  • Get practical experience with the Engineering & Computational Mathematics Clinic program.
  • Receive personalized career guidance from staff and faculty, as well access to a formal mentorship program with members of our MSFE Advisory Board.
  • This program is STEM designated, allowing international students who hold F-1 visas to apply for OPT work authorizations for a total of 36 months (an initial 1-year period and a 24-month OPT STEM extension) of paid work experience in the U.S. after graduation.
  • MSFE alumni go on to leadership roles in some of the most prominent financial firms and companies in the world, such as Goldman Sachs, Barclays, AIG, Blackrock, Western Asset Management, and the Capital Group.

Program At a Glance

32 units


*Actual completion times will vary and may be higher, depending on full- or part-time course registration, units transferred, and time to complete other degree requirements.


MS in Financial Engineering

Featured Courses

MATH 358
Mathematical Finance: Fixed Income and Derivatives

Pricing of equities, fixed income, credit, commodities, and currency derivatives, using stochastic calculus and numerical methods.

MATH 364
Machine Learning for Asset Pricing and Management

Basic optimization, machine learning, asset pricing and portfolio theory. Topics include mean-variance, mean-variance with learning, strategic asset allocation, linear factor models, linear programming, PCA, clustering, and deep learning.

Quantitative Risk Management

Value-at-Risk, expected shortfall, coherent measures of risk, risk aggregation, and capital allocation. Special focus is on credit risk, but different topics will vary according to current market needs.

MATH 453
Financial Time Series

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.

MGT 402
Asset Management Practicum

We will study how 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.

MATH 454
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.


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

Recommended Elective Courses

Spring Semester

Required Courses

Recommended Elective Courses

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)

Faculty & Research

  • Henry Schellhorn profile image

    Henry Schellhorn

    Professor of Mathematics
    Academic Director, Financial Engineering Program

    Research Interests

    Financial engineering, Credit risk, Stochastic analysis, Traffic models

  • John Angus profile image

    John Angus

    Professor of Mathematics

    Research Interests

    Probability, Statistics, Computing, Algorithms, Navigation, Systems Engineering, Mathematical Finance

  • Marina Chugunova profile image

    Marina Chugunova

    Professor of Mathematics
    Director, Institute of Mathematical Sciences
    Program Director, PhD in Engineering & Computational Mathematics

    Research Interests

    Surfactant-driven thin film flows in biomedical applications; Nonlinear parabolic equations; Stability problems in fluid dynamics; Scientific computations; Applied operator theory; Sturm-Liouville problems

  • Ali Nadim profile image

    Ali Nadim

    Professor of Mathematics
    Joseph H. Pengilly Chair in Mathematics

    Research Interests

    Fluid Dynamics, Mathematical Modeling, Scientific Computing

  • Qidi Peng profile image

    Qidi Peng

    Research Associate Professor of Mathematics

    Research Interests

    Statistical inferences, Stochastic differential equations, Stochastic modeling, Simulation, Machine learning, Approximation theory, Graph theory

  • Allon Percus profile image

    Allon Percus

    Professor of Mathematics

    Research Interests

    Discrete optimization; Network models; Statistical physics; Random combinatorial structures

  • Andrew Nguyen profile image

    Andrew Nguyen

    Adjunct Professor of Mathematics

    Research Interests

    Stochastic processes, Statistics, Risk management, Financial derivatives, Actuarial sciences, Statistical software

  • Jay Prag profile image

    Jay Prag

    Clinical Full Professor
    Academic Director
    Faculty Coordinator, Center for Business & Management of the Arts

    Research Interests

    Corporate Finance, Investments, Economics of Strategy, Macroeconomics

Where You Can Find Our Alumni

Financial Engineering exchange program - view of Lausanne bridge and cathedral in background

Exchange Program

The Financial Engineering program offers its students the exclusive opportunity to participate in an exchange program at the University of Lausanne, located in the beautiful country of Switzerland.

Known for its banking system and situated at the heart of Europe, Switzerland offers our students the opportunity to participate in financial forums and engage in stimulating financial discussions, both with world-renowned faculty and seasoned professionals.

Classes offered in the exchange program are comparable to those offered at CGU. These courses include Asset Pricing, Econometrics, International Finance, Probability, Stochastic Processes, Applied Corporate Finance, and Derivatives.

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