MS in Computational Finance

Master of Science 2010-2011

Computational Finance

The Charles H. Kellstadt Graduate School of BusinessThe Master of Science in Computational Finance is a joint degree between the College of Computing and Digital Media (CDM) and the Kellstadt Graduate School of Business (KGSB).

The objective of this program is to offer students the opportunity to acquire both the ability to understand existing financial models in a quantitative and mathematical way, and the ability to implement these models in the form of computer programs. This program differs from a regular MS in Finance because of a stronger mathematical component and the addition of an intensive computational component. The program aims to produce graduates with the required qualifications to become "quantitative financial analysts". The Computational Finance graduates will be able to apply these quantitative tools to solve complex problems in the areas of portfolio management, risk management, and financial engineering.

Learn more about admission to this program.

Online Learning Options
Some courses in this degree are available for review and playback via the CDM Course Online playback system (COL). If a course is COL-enabled, any student registered in the course has access to the course playback. Students are strongly encouraged to utilize the COL resource wherever available. Some courses are offered online. To complete this degree students may take any combination of courses offered online and on campus. For more information on online learning at CDM visit the Online Learning page. Information on online delivery of Kellstadt courses can be found on the Kellstadt Online Learning page. ​​
Degree Requirements
Students in this degree program must meet the following requirements:
  • Complete a minimum of 52 credit hours (generally 13 courses) beyond the Prerequisite Phase
  • Earn a grade of B- or better in each Prerequisite Phase course
  • Earn a grade of C- or better in all graduate courses beyond the Prerequisite Phase
  • Maintain a graduate level GPA of 2.50 or higher while pursuing their degree
  • Achieve a graduate GPA of 2.50 or higher at the completion of all other requirements

Students with a GPA of 3.9 or higher will graduate with distinction.

For DePaul's policy on repeat graduate courses and a complete list of academic policies see the DePaul Graduate Handbook in the Course Catalog.


Course Requirements
Prerequisite Phase
The goal of the prerequisite phase is to give students the background necessary for starting the graduate program. These prerequisite phase requirements can be fulfilled in one of three ways:
  • The student takes the course and earns a grade of B- or higher
  • The student takes a Graduate Assessment Exam (GAE) to test out of the course
  • The faculty advisor waives the course because of equivalent academic background or work experience.

All students are blocked from enrolling in Graduate Phase courses prior to completing their prerequisites. Students must submit an online Change of Status request (through myCDM) when the Prerequisite Phase is completed to inform the Student Services offices that the block can be removed.

MAT 150 Calculus I and MAT 151 Calculus II
or MAT 160 and MAT 161
or MAT 170 and MAT 171
CSC 261 Programming in C++ I and CSC 262 Programming in C++ II
or CSC 309 C++ for Programmers
CSC 202 Discrete Structures for Computer Science
orCSC 321 Design andn Analysis of Algorithms
CDM Foundation Courses
CSC 423 Data Analysis and Regression
CSC 425 Time Series Analysis and Forecasting
CSC 431 Scientific Computing
or CSC 485 Numerical Analysis
CSC 521 Monte Carlo Algorithms
Kellstadt Foundation Courses
ACC 500 Financial Accounting
ECO 555 Economics for Decision-Making
FIN 555 Financial Management
FIN 523 Investment Analysis
FIN 525 Portfolio Management
FIN 562 Risk Management
FIN 662 Derivatives Valuation
Advanced Phase
CSC 696 Master's Research
or CSC 697 Graduate Internship
or CSC 559 Software Engineering for Financial Markets
Major electives
Students must take 1 graduate CDM 500-Level course.