48 Units

18 Units
Finance Core Courses

18 Units
Mathematics Core Courses

12 Units
Elective Courses
The Financial Engineering Program at the Drucker School provides a flexible interdisciplinary curriculum

Forty-eight (48) units are required for the MSFE degree. The program can be completed in three semesters of full-time study.

The Internship in Financial Engineering can apply toward the management electives requirement.

Students with appropriate backgrounds can substitute additional electives for required courses.



Finance Core (18 units)

  Mathematics Core (18 units)

MGT 326 Financial Accounting
MGT 335 Corporate Finance

MGT 391 Introduction to Risk Management
MGT 402 
Asset Management Practicum

MGT 339 Financial Derivatives

  Math 251 Probability
Math 252 Statistical Theory
Math 463 Financial Time Series

Math 256 Stochastic Processes
Math 358 Mathematical Finance

Math 458A  Quantitative Risk Management
Math 458B Optimal Portfolio Theory (2 units)

Suggested Management &
Economics Electives

  Suggested Math Electives

ECON 384 Econometrics III
ECON 337 Behavioral Finance & Risk Management

MGT 307 Game Theory

MGT 327 Financial Statement Analysis

MGT 332 Energy Derivatives
MGT 334 Global Finance

MGT 340 Strategy

MGT 373 Financial Strategy and Policy

MGT 376 The Global Economy

MGT 383 Economics of Strategy

MGT 410 Entrepreneurial Finance

MGT 475 Selected Topics in Finance: Fixed Income

Math 265 Numerical Analysis
Math 282 Partial Differential Equations
Math 283 Mathematical Modeling
Math 261A Introduction to C++ (2 units)
Math 355 Linear Statistical Models
Math 359 Simulation
Math 361A Numerical Methods for Finance (2 units)
Math 361B Credit Risk
Math 366 Data Mining
Math 368 Advanced Numerical Analysis
Math 389 Discrete Mathematical Modeling
Math 392 Math Clinic
Math 452 Bayesian Data Analysis
Math 454 Statistical Learning


Course Planning Guide

The FE Program is flexible and offers all students, whether part-time, full-time, or fully-employed, the ability to decided on a semester-by-semester basis the schedule that will best fit with the demands of life. For example, a student can choose to take a full-time load, or four courses, in a semester when outside demands on time are lighter, and the following semester can opt to take one or two courses, if outside demands increase.

Below you will find the fall entry three (3) semester course planning guide.

1st Fall

1st Spring

2nd Fall

Probability 251 Stochastic Processes 256 Mathematical Finance 358
Financial Accounting 326 Statistics 252  OR
Asset Management 402
Corporate Finance 335
Financial Time Series 463
Introduction to Risk Mgt 391
Financial Derivatives 339
Elective Elective  

Math Clinics

Financial Engineering students have the opportunity to participate in client-based projects called Math Clinics. Clinic teams address problems of sufficient magnitude and complexity that their analysis, solution and exposition require substantial effort over the course of an academic year or full-time involvement over a summer. If problems require expertise from disciplines other than mathematics--such as engineering, physics or economics--advanced undergraduate or graduate students from these disciplines may join the Clinic team. The CGU Mathematics Clinic works closely with its counterparts at the Claremont Colleges, with clinic teams often combining graduate students and advanced undergraduates. Click here for more information on Math Clinics.

Data Analytics Concentration

Market demand for data analysts is expected to grow tremendously in the next 10 years. The trend is acute in every area of business, including financial engineering. With the huge quantity of data (“big data”) now available, financial engineers will be able to automatically detect patterns from accounting, financial, or web-based data. With access to enormous quantities of data, financial engineers need knowledge and powerful methods for extracting quantitative information, particularly on volatility and risk.

The Financial Engineering Data Analytics concentration focuses on the theory and tools needed to understand, extract, and model data. Students will learn the concepts for financial markets and economic data, will work with real data exercises, and will integrate graphical and analytical methods for modeling and diagnosing modeling errors.

Students will be required to take 3 of the courses listed below in Data Analytics:

MATH 252 Statistics
MATH 355 Linear Statistical Models

MATH 366CM Data Mining
MATH 452 Large Scale Inference

MATH 454 Statistical Learning


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