Students who wish to enter the business world focused on the quantitative aspects of finance may consider earning a graduate degree in computational finance. Individuals with this interest have a range of options at the master's and doctoral levels. Here, prospective students can read more about some degree options, common courses in computational finance programs, and admission requirements for these degrees.
Computational Finance Degree Options
Master of Science
One popular option for students who wish to study computational finance at the graduate level is a Master of Science program in computational finance or computational finance and risk management. Students can typically complete this program in two years. MS programs often help students develop skills in the areas of machine learning, risk management, and portfolio optimization. Computer programming languages may be infused throughout the curriculum.
Master of Business Administration
Another possible course of study is to earn a Master of Business Administration (MBA) with a focus in computational finance. An MBA program typically requires two years of study to complete. Students take core MBA classes and then choose electives focused on computational finance skills. Many business schools incorporate opportunities for hands-on learning, such as a practicum or case competitions.
Doctor of Philosophy
Students primarily interested in pursuing careers focused on research and teaching may consider earning a Doctor of Philosophy, or Ph.D., in applied mathematics with a focus on computational finance. Depending on students' research interests, a Ph.D. program in applied mathematics is typically completed in five years of study. These Ph.D.s require the development of core competencies in mathematics, followed by elective courses focused on mathematical applications to finance. Common requirements for degree completion include qualifying examinations as well as the preparation and defense of a thesis.
Computational Finance Core Courses
Within each of these degree options, students take a range of courses designed to introduce them to key concepts in computational finance. Read on to learn more about some of these courses.
A course in financial optimization may provide an introduction to the major classes of optimization models, including linear, quadratic, and dynamic optimizations. Specific topics could include Bellman equations, foreign exchange, and GARCH model fitting. Assignments might require the optimization of real-world data through homework sets and projects.
Financial Data Science
This course is designed to provide students with a framework for using statistical procedures to extract relevant information from financial data. Specific statistical procedures such as chi-square tests and simple linear regression may be utilized. The course could emphasize programming languages and how they are useful in the analysis of big data.
Business professionals must be able to adequately communicate their findings or recommendations in computational finance. This course may provide them with opportunities to develop these communication skills, both orally and in writing. Hands-on assignments might include role plays, interviews, and impromptu presentations.
Fixed Income Securities
A fixed income securities course may provide students with techniques to analyze and manage fixed income portfolios. Students might learn how to value securities and price interest rate derivatives through an examination of relevant computational and mathematical methods, such as the binomial tree model.
This course could introduce students to the range of risks that may be experienced by various financial entities. Specific topics may include credit risk, volatility, and operational risk. A potential assignment is the modeling of some of these risks.
Admission requirements vary depending on the university and the degree sought. MS programs frequently require GRE or GMAT results, transcripts, a statement of purpose, resume, and recommendations. Undergraduate coursework in calculus, statistics, and computer science may be required. MBA programs typically require students to submit transcripts, GMAT or GRE scores, a resume, statement of purpose, and letters of recommendation. An interview or video essay may also be a component. Ph.D. admissions requirements usually include a bachelor's degree in a quantitative area, transcripts, GRE scores, recommendations, and a personal statement.
Many options are available for students who wish to earn graduate degrees in computational finance. Students pursuing MS, MBA, Ph.D. programs are exposed to a range of courses in statistics, risk management, and data science to promote understanding of this discipline.