Carnegie Mellon University

Curriculum

MSCF’s highly-integrated, interdisciplinary curriculum is well-balanced between theory and practice. Programs “owned” by business schools can be strong on financial markets but pay less attention to the mathematical modeling. Conversely, programs “owned” by math departments are often highly theoretical and less focused on “real world” applicability.

The MSCF curriculum is constantly changing to meet the needs of the financial markets. While stochastic calculus and computational techniques such as Monte Carlo simulation, optimization, and the numerical solution of partial differential equations prepare students to create and validate the mathematical models underlying much of the finance industry, our statistics and programing courses prepare students for careers in data-driven algorithmic trading, risk management and quantitative portfolio management.

Indeed, the MSCF degree will better prepare you for a position as a data scientist in the finance industry when compared with either a MS in Data Science which covers a broad range of applications or an MS in Business Analytics which focus is on improving a firm's performance using data-driven decision making. Neither of these programs has the laser focus of MSCF, applying machine learning and other data science tools to quantitative finance. Taught with mathematical rigor coupled with the necessary computational skills provided by our computer science courses, students emerge from our program exceptionally well prepared for data scientist careers in the finance industry.

The MSCF course of study is a blend of traditional lectures, individual and group projects, and presentations. All MSCF courses are developed expressly for the intended career paths our students, with introductory courses in the early fall leading to core courses throughout the first year followed by additional core courses and various electives in the final semester, allowing you to focus on the area of quantitative finance of most interest to you.

In the beginning of August, four weeks before the start of the degree program, the “MSCF Prep” session provides preparatory classes in math, probability and programming. In addition, you will attend lectures in financial markets, basics of financial accounting and accounting for derivatives, and be offered presentations on the various career paths in quantitative finance. Working with your career counselors, you will build your resume and learn networking and interviewing skills via MSCF’s full-time communications coach. You will also begin training with Deutsche Bank traders for the Deutsche Bank Trading Competition.

MSCF Probability
Prep
MSCF Math &
Markets Prep
MSCF Programming
Prep
Communication
Prep
Financial
Markets
Linear
Algebra

Over the fall and spring of your first year, you will learn traditional finance theories of equity and bond portfolio management, the stochastic calculus models on which derivative trading is based, Monte Carlo simulation methods for computing prices and risk measures, statistical methodologies including regression and time series, and financial data science. C++, R and Python are woven throughout the curriculum to provide you with the software skills you will need throughout your career. A presentations course will help you communicate your ideas to your peers. The Deutsche Bank Trading Competition, offered on the Interactive Brokers Traders Workstation’s simulated trading platform, provides real-world trading experience (and cash prizes). The Financial Engineering course requires you to work on a team to solve a problem and sell your solution. Throughout, courses offered by the Communication Development Program will build your confidence as you learn deportment, networking and effective writing — in short, how to function on Wall Street.

Mini 1:

Financial Data
Science I
Financial
Computing I
Fixed
Income
MSCF
Investments
MSCF Business
Communication I

Mini 2:

Financial Data
Science II
Financial
Computing II
MSCF
Options
Multi-Period
Asset Pricing
MSCF Business
Communication I

Mini 3:

Statistical Machine
Learning I
Financial
Computing III
Simulation Methods
for Option Pricing
Stochastic Calculus
for Finance I
MSCF Business
Communication II

Mini 4:

Statistical Machine
Learning II
Risk
Management I
Stochastic Calculus
for Finance II
Presentations for
Computational Finance
MSCF Business
Communication II
Deutsche Bank
Trading Competition

You will learn about the inner workings of the financial markets through your summer internship, returning to the program in the fall with a much better sense of the full-time position you wish to pursue. Recruiter interest in our students is strong and our career counselors will work closely with you to assist you in the internship search. Over the last five years, 98% of our students have obtained internships, the great majority in the United States.

MSCF Summer Internship

For the final semester, following your summer internship, you will take a mixture of required and elective courses. The elective courses permit you to specialize in financial computing, asset management, algorithmic trading, and risk management.

Mini 1:

Financial
Optimization
Financial Time
Series Analysis
MSCF Studies in
Financial Engineering


Electives: Choose one of three
Advanced
Derivative Models
 Numerical
Methods
Risk
Management II

Mini 2:

Macroeconomics for
Computational Finance

Electives: Choose three of four
Asset
Management
Financial
Computing IV
Market Microstructure
& Algorithmic Trading
Statistical
Arbitrage



The MSCF program reserves the right to change course times and offerings.
Students will be notified of any changes via email.