Master of Science in Quantitative and Computational Finance
The Master of Science degree program in Quantitative and Computational Finance (MS QCF) is a multidisciplinary program under the provost of the Georgia Institute of Technology, with home units in the College of Business, the School of Mathematics, and the School of Industrial and Systems Engineering.
The main objective of the MS QCF degree program is to provide students with the practical skills and theoretical understanding they need to be leaders in the formulation, implementation, and evaluation of the models used by the financial sector to structure transactions, manage risk, and construct investment strategies.
The MS QCF program is well structured both to cover the fundamentals needed to understand and model a wide variety of problems in finance and to allow specialization to build expertise in specific approaches, techniques, and problem areas. For the fundamentals, the MS QCF program emphasizes both foundational concepts within finance and also the principles and techniques needed for the formulation, implementation, and testing of financial models. The program is not just centered on one type of problem; students develop expertise for a range of career paths that use quantitative and computational reasoning. For their area of specialization, students are encouraged to develop expertise that draws on the strengths present in the many related quantitative, computational, and mathematical areas present at Georgia Tech.
The prerequisites of the MS QCF program include:
- interest in the problems of finance, and a high level of mathematical ability that has been demonstrated within past performance on appropriate coursework and standardized testing;
- mathematical background - a working knowledge of calculus (differential and integral calculus of one variable, multivariate calculus, fundamentals of linear algebra and linear systems of equations, and differential equations) and undergraduate calculus-based probability and statistics;
- basic programming background - basic knowledge of a programming language, such as MatLab programming, Python, Java, Visual Basic, C, C++, or Fortran; and
- Institute and academic unit requirements for admission to graduate study.
MS in Quantitative and Computational Finance Curriculum Requirements
Required Core Courses (18 semester hours)
MGT 6078 Finance and Investments
MGT 6081 Derivative Securities
MATH 6635 Numerical Methods in Finance
ISYE/MATH 6759 Stochastic Processes in Finance I
ISYE/MATH 6767 Design and Implementation of Systems to Support Computational Finance
ISYE/MATH/MGT 6769 Fixed Income Securities
Nine semester hours from the following:
ISYE 6673 Financial Optimization Models
MATH 6235 Stochastic Processes in Finance II
MGT 6090 Management of Financial Institutions
ISYE/MATH 6783 Statistical Techniques of Financial Data Analysis
ISYE/MATH/MGT 6785 The Practice of Quantitative and Computational Finance
MGT 7061 Empirical Finance
Nine semester hours of free electives at the 6000 level or higher
Total semester hours: 36
For the nine semester hours of free electives at the 6000 level or higher, students choose at least three additional electives from the electives categories or from other courses. Students are encouraged to choose electives to develop expertise within a specific area such as statistical data analysis, economic analysis, finance, risk management/optimization, or model implementation. It is strongly recommended that students who do not have previous coursework in economics take ECON 6100 Economic Analysis for Managers (or its equivalent).