The Financial Engineering Program at the Drucker School provides a flexible interdisciplinary curriculum. You have the opportunity to tailor your study to align with your professional goals within general finance, quantitative finance or data analytics.
Forty (40) units are required for the MSFE degree. The program can be completed in three semesters of full-time study.
New students are required to show competency in Financial Accounting and Probability prior to enrollment in coursework via the following options:
- Have taken a Financial Accounting course in their undergraduate coursework or recently online
- Pass a probability waiver exam or have taken a Probability course in their undergraduate coursework or recently in a community college, college or university
New students are required to have successfully passed both courses prior to the start of the program or within the past 5 years and received a grade of a B or better. Students who do not fulfill the competency requirements for probability will have to take a probability course at CGU for 4 units and would have to pay the required tuition. The same requirements apply for Financial Accounting.
An internship in Financial Engineering can apply toward the management electives requirement.
Students with appropriate backgrounds can substitute up to 8 units of elective coursework for required courses. Course waivers are determined during academic advising sessions and approved by faculty.
MSFE Unit Breakdown
|Finance Core Courses||14 Units|
|Mathematics Core Courses||14 Units|
|Elective Courses||12 Units|
|Total Degree||40 Units|
The FE program takes from 18 months to two years to complete. Scheduling is flexible, and the degree can be pursued either part-time or full-time.
Introduction to Risk Management
Financial Time Series*
Elective (Math or Finance)
Asset Management Practicum
Quantitative Risk Management OR Optimal Portfolio Theory
Elective (Math or Finance)
*Either Statistics or Financial Time Series is a mandatory core requirement.
The goal of the course is to develop understanding of financial decision making, including investment decisions, financing decisions, and their interaction. The course will expose you to the underlying framework of corporate finance including valuation, market efficiency, portfolio theory, agency costs, and information costs. The course will relate financial management to the structure of financial institutions in the U.S. Finally, the course will survey special topics including option pricing, mergers and acquisitions, hedging, and international finance.
In this course, students develop an understanding of financial derivative instruments and their applications to corporate strategy and risk management. Throughout the course, we distinguish between using derivatives to appropriately manage risk and using them for speculation. We emphasize the perspective that derivative instruments are problem-solving tools that, when used correctly, can create value for financial and non-financial corporations. We develop the basic mathematical tools necessary for analysis, design, pricing, and implementation of derivatives in a managerial context. We cover forward, future, option, and swap contracts, hedging, arbitrage, and derivatives-pricing models. In addition, we introduce securitization, real options, and risk management. Through case preparation and discussion, students learn to model and evaluate derivative instruments and risk exposure.
Corporate Finance or permission of instructor.
Introduction to Risk Management
The course will provide a comprehensive introduction to risk management from the perspective of both financial and non-financial institutions. It covers the design and operation of a risk-management system, the technical modeling within that system, and the interplay between the internal oversight and the external regulatory components of the system.
A basic understanding of statistics is helpful
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. Practice of actual asset management involves hands-on investment of equity securities in a portion of the CGU endowment portfolio which has been set aside for the educational benefit of the class. Asset management firms establish/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.
This course will cover in depth the mathematics behind most of the frequently used statistical tools such as point and interval estimation, hypothesis testing, goodness of fit, ANOVA, linear regression. This is a theoretical course, but we will also be using R statistical package to gain some hands on experience with data.
Continuation of Mathematics 251 Probability. Properties of independent and dependent random variables, and conditional expectation. Topics chosen from Markov processes, second order processes, stationary processes, ergodic theory, Martingales, and renewal theory.
This course will cover the theory of option pricing, emphasizing the Black-Scholes model and interest rate models. Implementation of the theory and model calibration are covered in the companion course, Numerical Methods for Finance. We will see the binomial no-arbitrage pricing model, state prices, Brownian motion, stochastic integration, and Ito’s lemma, the Black-Scholes equation, risk-neutral pricing and Girsanov theorem, change of numeraire and two term structure models: Vasicek and LIBOR.
Mature understanding of Multivariable Calculus and Probability and permission of the instructor. Some familiarity with simple partial differential equations would be helpful.
Financial Time Series
This course will cover standard methods in handling time series data. These include univariate arima and garch models. Some multivariate models will also be discussed.
Probability and Statistics
Quantitative Risk Management
This course will focus on the calculation of Value-at-Risk, risk theory, and extreme value theory. We will also study coherent measures of risk, the Basle accords, and, if time allows, the role of BIS. There will be a practical assignment with data coming from Riskmetrics. We will discuss practical issues following the 2008-2009 financial crisis.
Stochastic Processes & knowledge of derivatives
Optimal Portfolio Theory (2 units)
This course will touch briefly on the (one-period) CAPM. Then we will move to the dynamic CAPM (Merton’s model), first in discrete time, then in continuous time. We will also cover related approaches favored by practitioners, such as Black-Litterman. We will also cover estimation problems, and, if time allows, Roll’s critique of the CAPM. Along the way, we will study dynamic programming in discrete and continuous time.
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.
Dual Degree in Financial Engineering and Mathematics
Financial Engineering students have the option of applying to the dual MSFE/MS Math dual degree program. The combination of the two degrees allows students to enhance their quantitative knowledge and broaden their professional opportunities. Students who add the MS Math degree may complete both programs in two years.
Area of 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. Detailed course descriptions are available on the Institute for Mathematical Sciences page. Students will be required to take 3 of the courses listed below in Data Analytics:
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. Detailed course descriptions are available on the Institute for Mathematical Sciences page.
Students will be required to take 3 of the courses listed below in Data Analytics:
Sampling of Electives
The Financial Engineering Program at the Drucker School provides a flexible interdisciplinary curriculum. Forty (40) units are required to complete the degree. Twelve (12) of those units are elective courses, which you can choose from the options below.
Full descriptions for the mathematics courses are available on the Institute for Mathematical Sciences page.
The Study Abroad Program is open to all Drucker students, but 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.