Why Study Mathematical Finance
The Mathematical Finance program integrates mathematical, statistical, financial, computational and risk related techniques with professional skills to succeed in the financial world.
Students from diverse backgrounds such as economics, business, commerce, physics, marketing, mathematics, finance, accounting, statistics, actuarial science, computer science, electronics & electrical engineering, pharmacy, commerce, etc., have successfully completed their Mathematical Finance program and are currently working in industry or pursuing Ph.D.
Many of the recent graduates are working in big financial firms, such as Intel, Goldman Sachs, Nasdaq, Amazon, Citibank etc.
M.S. / PSM Computer Science and Quantitative Methods: Mathematical Finance Concentration is designed for students or working professionals with a bachelor’s degree to learn about various mathematical/statistical financial models, analyze investments and the associated risks facing all institutions. This program prepares students to pursue many different paths, such as, Financial Analyst, Data Scientist, Quantitative Analyst, Actuarial Scientist, Credit Data Analyst, Risk Analyst, Operation Research Analyst, Climate Change Policy Managers, Investment Fund Managers etc. The program is offered both online and on-campus.
The APSU Mathematics and Statistics Department has dedicated full-time faculty members and features small class sizes. All classes are taught by professors and instructors satisfying APSU Faculty Qualifications Matrix. Many classes are conducted in modern computer labs, and all classrooms are “smart” classrooms, allowing projector-based demonstrations and lectures.
The faculty in the Mathematical Finance concentration have experience teaching mathematics/statistics at post graduate level. All full-time professors have completed terminal degrees in various mathematics/statistics fields and part-time faculty members have many years of real-world experience in different mathematical/statistics disciplines. Many faculty are engaged in multi-disciplinary research and are active in local, state, and national professional mathematics organizations.
Department of Mathematics and Statistics is one of the institutions in Tennessee that offers, in its Bachelor’s (B.S.) degree, a variety of concentrations (Actuarial Science, Statistics, Data Science), and multiple Master’s degree (M.S.) and Professional Science Management (Predictive Analytics, Mathematical Finance, Mathematical Instruction). Currently there are more than 80 students in the Master’s program. Mathematical Finance and Predictive Analytics are offered 100% online as well as on-campus. Students have frequent opportunities to attend conferences and present their research while working closely with the mathematical finance faculty.
With the advent of Information technology, AI, and Big data, there has been an increase in the demand of applied mathematicians across a range of sectors. This huge demand in the market is due to the universal need for graduates with strong problem solving and logical thinking skills, and the ability to communicate complex ideas in a clear and unambiguous way. Students graduating from the Mathematical Finance program are provided the requisite knowledge to succeed in the current market. This is evident from our recent Mathematical Finance graduates who are currently working in world class leading financial, banking, actuarial science, and government institutions.
Admission Requirements
For information related to admission requirements (MS or PSM) or to view the courses within the MS or PSM program, please visit the graduate bulletin.
What Will I Learn
- Demonstrate an advanced understanding of the theoretic underpinnings of financial mathematics, probability theory, numerical analysis, and computational methods in finance.
- Demonstrate critical thinking, specifically employ appropriate analytical methods, and apply critical reasoning processes to describe and model financial contracts.
- Demonstrate the knowledge and understanding of mathematical finance by doing a particular research topic or doing an internship.
- Be able to effectively communicate mathematical finance ideas and results through contexts such as seminars, teaching, outreach, publications, and cross-disciplinary work.
Sample Course Plan
Computer Science and Quantitative Methods: Mathematical Finance, MS
Computer Science and Quantitative Methods: Mathematical Finance, PSM