Overview

https://www.msmf.miami.edu/

The Master of Science in Mathematical Finance program is dedicated to producing technically trained professionals with an understanding of how to analyze and value complex investments, and assess the associated risks. Over the course of three semesters of study, the students receive rigorous training in mathematics, especially in the area of probability and stochastic calculus, in statistical analysis, and in computation, together with an overview of the common financial instruments and the institutional operation of markets and exchanges.

The financial landscape is constantly changing, and we design the MSMF curriculum to equip students with skills and knowledge that will provide the foundation for their future success. Our program seeks the proper balance between the mathematical and statistical theory, programming practice and financial applications.

Admission Requirements

Here is a list of the course based admissions requirements. For more information about admission, please visit our website.

  • 1 semester of Linear Algebra
  • 1 semester of Differential Equations
  • 1 semester of calculus-based Probability and Statistics

Curriculum Requirements

Core Courses
MTH 642Statistical Analysis3
MTH 643Statistical Analysis II with Financial Applications3
MTH 645Optimization Methods3
MTH 647Introduction to Mathematical Finance3
MTH 648Stochastic Calculus with Application to Finance3
MTH 649Computational Methods of Finance3
FIN 650Financial Investment2
FIN 651Advanced Topics in Investments2
Electives12
Computer Science, Engineering, and Mathematics Electives (3-9 credits)
Introduction to Parallel Computing
Introduction to Artificial Intelligence
Machine Learning
Neural Networks
Partial Differential Equations I
Partial Differential Equations II
Numerical Linear Algebra
Quantitative Risk Analysis
Machine Learning in Quantitative Finance
Mathematical Probability
Finance Electives (2-6 credits)
Quantitative Finance and Market Microstructure
Alternative Investments
International Finance
Corporate Finance
Financial Institutions
Financial Modeling
Other Business Electives (0-3 credits)
Financial Reporting and Control in the Healthcare Industry
International Monetary Economics
Game Theory in Economic Applications.
Business and Security Valuation
Fixed Income Markets and Analysis
International Financial Management
Total Credit Hours34

Sample Plan of Study

3-semester MSMF 

Plan of Study Grid
Year One
FallCredit Hours
MTH 642 Statistical Analysis 3
MTH 647 Introduction to Mathematical Finance 3
FIN 650 Financial Investment 2
Elective 1 3
 Credit Hours11
Spring
MTH 643 Statistical Analysis II with Financial Applications 3
MTH 648 Stochastic Calculus with Application to Finance 3
FIN 651 Advanced Topics in Investments 2
Elective 1 3
 Credit Hours11
Summer
Summer Internship or Project (Optional)  
 Credit Hours0
Year Two
Fall
MTH 645 Optimization Methods 3
MTH 649 Computational Methods of Finance 3
FIN Electives 3-6
Additional Elective (If Needed) 1 3
 Credit Hours12-15
 Total Credit Hours34-37

Mission

The Master of Science in Mathematical Finance program is dedicated to producing technically trained professionals with an understanding of how to analyze and value complex investments, and assess the associated risks. Over the course of three semesters of study, the students receive a rigorous training in mathematics, especially in the area of probability and stochastic calculus, in statistical analysis, and in computation, together with an overview of the common financial instruments and the institutional operation of markets and exchanges.


The financial landscape is constantly changing, and we design the MSMF curriculum to equip students with skills and knowledge that will provide the foundation for their future success. Our program seeks the proper balance between the mathematical and statistical theory, programming practice and financial applications.

Goals

  • Provide future finance professionals with the advanced quantitative skills required to understand, evaluate and price modern financial instruments. Such skills include both analytic techniques of mathematical finance, and computer-based simulation techniques.
  • Expose participants to the key statistical methods, and specifics of applying these methods to working with financial data. 
  • Impart the necessary hands-on software and programming skills to solve various optimization and simulation problems arising in financial setting.

Student Learning Outcomes

  • Students will demonstrate advanced knowledge of risk-neutral approach to pricing financial instruments, discrete and continuous-time frameworks of modern mathematical finance, and common financial derivatives.
  • Students will master the tools of statistical analysis and statistical software packages and be able to apply them to various financial datasets.
  • Students will demonstrate working knowledge of software and programming tools to use optimization and simulation techniques in financial setting master the common models of portfolio analysis, as well as the quantitative approach to risk models.