Master's degree programs in computational finance are usually interdisciplinary programs that culminate in a Master of Science degree. These programs may be completed in as little as one year and prepare students for a variety of finance and business-related careers. Here, we explore these degree programs, including common courses and common admissions requirements.
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Information for Master's Degree Programs in Computational Finance
Students in master's degree programs in computational finance usually do not have to complete a final thesis but may take a final comprehensive exam and/or participate in hands-on learning experiences through internships and other opportunities. These degree programs often provide elective courses for students to individualize their plan of study, but below we discuss a few of the common course topics.
Principles of Finance
Courses in the principles of finance are designed to teach students the foundational concepts in finance and financial management. Students spend time examining finance decisions and all of the variables that go into choosing which projects to pursue and how to fund them. These courses may also discuss topics in financial reporting, financial markets, investment and regulation.
Students in these programs may take one or more courses in computational finance that allow them to explore the subject through case studies and group projects. Some of these courses may focus on the programming aspects of computational finance and allow students to learn about the data structures and algorithms in programming, different programming methods and data analysis. Students in these courses may analyze large data sets to try and solve issues in areas like credit risk, asset management and more.
Students may take broad courses in derivative securities that cover the different types of derivatives and how they function, but advanced courses in derivatives focus on the theories, models and financial-engineering aspects of derivatives. Students examine the pricing, uses and contracts for derivatives and generally need a background in calculus for these courses. Specific topics may include local and stochastic volatility models, credit default swaps, fixed-income contracts and more.
Courses in fixed income explore securities in fixed income markets and how they are valued or priced. These courses are heavy in mathematics and allow students to experiment with different models and techniques for valuing these securities and learn about the issues with various methods. These courses may cover specific topics in convexity, yield, duration, Ho-Lee and Black-Derman-Toy models and more.
Finance and Investments
Courses in finance and investments focus on the analytical skills needed to make good investment decisions. Students in these courses discuss the concepts needed for quantitative portfolio management, such as factor models and mean-variance optimization. These courses may touch on the ethics of investing, but also discuss topics in risk, asset allocation, market efficiency, pricing anomalies and more.
Common Entrance Requirements
Most master's degree programs in computational finance require applicants to hold a bachelor's degree and submit their official transcripts, GRE or GMAT scores, letters of recommendation, a personal statement and a resume or CV with their application. Some of these degree programs may also require applicants to go through an interview process with the admissions committee. Work experience is not generally required for these degree programs, but students may be expected to have some experience with programming and probability and mathematics coursework. Some programs may have specific course prerequisites for admission, such as linear algebra, calculus or programming.
Students may pursue a Master of Science in Computational Finance in as little as one year to learn the analysis methods for various business topics. These degree programs provide hands-on learning and prepare students for a wide range of careers.