Nov 24, 2024  
Rensselaer Catalog 2019-2020 
    
Rensselaer Catalog 2019-2020 [Archived Catalog]

Master of Science in Quantitative Finance and Risk Analytics


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The purpose of this degree is to provide students with the knowledge and essential skills to respond to the changes and new challenges that characterize the fast-changing world of Quantitative Finance and Risk Analytics. The goal of the program is for students to master cutting-edge financial theory as well as advanced analytical and quantitative techniques that have become key to the success of the new breed of financial experts. Students will be exposed to emerging concepts, practices, and techniques in the finance industry through rigorous training in empirical research and modeling, using a variety of professional databases and computer software packages.

The degree emphasizes three skill areas—business skills in finance, technical skills, and computational skills. Within these three skill areas students will be able to develop expertise in areas such as quantitative financial analysis and financial risk assessment and management.

The program requires five foundation courses and five elective courses from across three skills areas. The QFRA Program is designed to allow for maximum flexibility for students from a variety of backgrounds wishing to pursue rigorous study in quantitative finance and risk analytics. It requires 30 credit hours for students with a Finance or Technical undergraduate background.

Prerequisites: Basic foundation of mathematics and statistics. Students may take a suitable prerequisite course within Lally if such a course is offered and is approved by the QFRA Program Director. Students with college-level calculus and statistics courses (the equivalent of 6 credit hours) will normally have fulfilled this prerequisite, as will students with undergraduate backgrounds in finance, management, business, economics, and technical fields.

Foundation courses are basic courses in finance and quantitative methods that contain concepts that are prerequisite to understanding the principles of Quantitative Finance and Risk Analytics. These foundation courses are required for all students without undergraduate business degrees and for students whose backgrounds did not include coverage of comparable material. Students in Quantitative Finance and Risk Analytics with business undergraduate degrees may waive the Financial Management I course with the consent of the Program Adviser(s) if they have sufficient relevant undergraduate work. A student can waive this foundation course if he or she earned a B or better in an introductory finance course as well as a B or better in one higher level finance course. If this or any other course is waived, it must be replaced with some other course from the courses listed below. Therefore, waivers of any of these Foundation Courses will require substitutions from the Elective Courses lists.

A two-semester Professional Development Workshop series is also required to help students develop business communication, teamwork, leadership, and job search skills.

Outcomes of the Graduate Curriculum

Students who successfully complete this program will be able to:

  • utilize a core set of analytical skills in finance.
  • utilize a core set of analytical skills in economics and accounting.
  • utilize a core set of analytical skills in statistical analyses.
  • utilize modeling skills to conduct quantitative analysis for financial engineering and the analysis of financial risk.
  • utilize computational tools to facilitate data analysis for financial engineering and the analysis of financial risk.
  • demonstrate knowledge of roles and functions of financial institutions and their regulatory settings.
  • demonstrate knowledge of financial markets, their roles and functions in dealing with financial risks.
  • demonstrate knowledge of valuation of financial instruments for investment, trading and hedging decisions.
  • develop strategies for investment and management of risk.

Five Required Core Courses


Business Core Course


6 credits

Computational Core Courses


6 Credits

Technical Core Course


3 Credits

Five Electives from Three Skill Tracks


15 Credits

Students may elect courses from an evolving list of courses (example list below) as approved by the adviser in order to best meet their academic goals.

Computational Skills Area


  • ECSE 4962 - Introduction-Machine Learning Credit Hours: 3

Two Required Professional Development and Career Workshops


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