MS in Mathematical Finance & Financial Technology

The MS in Mathematical Finance & Financial Technology (MSMFT) is a full-time, three-term, 39-unit program with a common core during the first term. In the two remaining terms, students complete elective courses consistent with their academic and career goals.

Learning Outcomes

The MS in Mathematical Finance & Financial Technology (MSMFT) Program aims to produce graduates with expertise in the following domains:

• Computational Expertise
  Students develop advanced programming skills in modern languages used in the financial services industry: Python, R, C++, MATLAB, SQL.
• Financial Econometrics & Statistics
  Students review the fundamentals of probability and statistics required for estimation, then econometrics. Students learn advanced financial econometrics methods such as Bayesian econometrics, estimation by simulation, volatility forecasting, factor models, etc.
• Stochastic Analysis & Dynamic Programming
  Students master stochastic calculus, stochastic differential equations, and dynamic programming. These techniques are required to develop and understand modern asset pricing theory.
• Data Science & Data Analysis
  Students learn to work with high-frequency or large data sets and analyze them via machine-learning techniques. Numerical methods, such as simulation, are employed for computation.
• Market Structure & Financial Instruments
  Students must have a good understanding of the functioning of financial markets and the financial instruments traded in these markets (futures, options, swaps, etc.). Students are introduced to the institutional details and regulatory structures associated with modern financial markets.
• Risk Management
  Risk management is one of the core disciplines of modern finance. Students learn how to use specific instruments to manage risk (derivatives, fixed-income instruments, etc.). They master specific dimensions of risk management (market risk, credit risk, operational risk, and counterparty risk). Practical interaction with taxation is also studied.
• Derivatives
  Derivatives are used to manage risk (see learning goals in Risk Management and Credit Risk). Their complexity is such that a field of finance—in academia and in the industry—is devoted to understanding their pricing. We have made a specific learning goal: the ability to know, understand, and use the most sophisticated derivatives pricing models.
• Credit Risk
  The measurement and management of credit risk is a core sub-discipline in finance, with its own set of theoretical models. Students are expected to be familiar with the theory of credit risk at an advanced level.
• Portfolio Theory
  Portfolio theory addresses the construction and dynamic adjustment of portfolios of assets that are optimal given one or more objectives. Portfolio theory is part of the core of modern theoretical finance. Students are expected to understand all aspects of portfolio theory, including standard mean-variance theory, dynamic asset allocation, asset-liability management, and lifecycle finance.
• Financial Technology
  Students should acquire hands-on exposure to the most recent developments in financial technology, including distributed ledgers (blockchains), digital currencies, robot-advising, and peer-to-peer lending. In addition, students are expected to develop a sound understanding of the advanced techniques for improving computational performance, such as parallel computation and GPU acceleration. In addition to the data analysis techniques described in the goals for Financial Econometrics & Statistics and Data Science & Data Analysis, students are exposed to the latest machine-learning techniques, including tree methods, deep learning, and text analysis.

MS in Mathematical Finance & Financial Technology Curriculum—39 units

Required Core—18 units:

• QST ES 620 Design Your Career (0 units), taken online in summer before matriculation
• QST ES 621 Design Your Career (0 units), taken the first fall
• QST ES 622 Design Your Career (0 units), taken the first spring
• QST ES 630 Communicating Financial Recommendations (1.5 units)
• QST MF 610 Mathematical Finance Career Management (.5 unit, taken each term for a total of 1.5 units)
• QST MF 702 Fundamentals of Finance (3 units)
• QST MF 703 Programming for Mathematical Finance (3 units)
• QST MF 790 Introduction to Stochastic Calculus (3 units)
• QST MF 793 Statistics for Mathematical Finance (3 units)
• QST MF 728 Fixed Income Securities (3 units)*

*Students may waive this requirement with the approval of the Program Faculty Director.

Financial Technology Elective—3 units

Students must choose one course from the following Financial Technology electives:

• QST MF 740 Economics of FinTech
• QST MF 810 Advanced Programming for Financial Analytics
• QST MF 815 Advanced Machine Learning Applications for Finance
• QST MF 821 Algorithmic and High-Frequency Trading
• QST MF 840 Data Analysis and Financial Econometrics
• QST MF 850 Deep Learning and Statistical Learning

General Electives—18 units

• Students must choose an additional six 3-unit electives in order to reach the 39-unit program minimum.

Electives

• QST AC 860 Accounting for Risk Management
• QST MF 730 Dynamic Portfolio Theory
• QST MF 731 Corporate Risk Management
• QST MF 740 Economics of FinTech
• QST MF 770 Advanced Derivatives
• QST MF 772 Credit Risk
• QST MF 796 Computational Methods of Mathematical Finance
• QST MF 810 Advanced Programming for Financial Analytics
• QST MF 815 Advanced Machine Learning Applications for Finance
• QST MF 821 Algorithmic and High-Frequency Trading
• QST MF 825 Portfolio Construction
• QST MF 840 Data Analysis and Financial Econometrics
• QST MF 850 Deep Learning and Statistical Learning

Students must pick elective courses from the approved list of courses. Any additional courses beyond 13-units-per-term or 39 units in total must be approved in advance by the Program Faculty Director. If a student is interested in taking an elective outside of the program, either at Questrom or at another college at BU, they must have the approval of the Program Faculty Director in consultation with the Mathematical Finance & Financial Technology Program Development Committee.

Academic Standards

Satisfactory Academic Progress

The Specialty Master’s & PhD Center monitors students’ academic performance at the end of the fall and spring terms. A student must maintain a cumulative grade point average (CGPA) of at least 2.70 (on a 4.0 scale) to remain in good academic standing during their studies and to graduate. Coursework taken outside Questrom School of Business, which does not count toward the MS in Mathematical Finance & Financial Technology degree, will not be calculated into the student’s CGPA.

Student academic progress will be assessed against this standard at the mid-point and at the end of each term by the MSMFT Program Development Committee. The review may result in a warning, academic probation with explicit expectations for improvement, or discontinuation from the program. A student who fails to make sufficient progress has the right to appeal. The process for appeal is fully described in the MSMFT Student Handbook.

Degree Requirements

To qualify for the MS in Mathematical Finance & Financial Technology, students must:

• Complete all required courses for a total of 39 units. Note that 1-unit Curricular Practical Training (CPT) courses for international students cannot be used to satisfy degree requirements.
• Have a cumulative GPA of at least 2.70.
• Have no “I” grades or no “MG” grades in courses counting toward the degree.

MS in Mathematical Finance & Financial Technology and Graduate Certificate in Advanced Financial Technology Concurrent Enrollment

For students who are pursing both the MS in Mathematical Finance & Financial Technology and the Graduate Certificate in Advanced Financial Technology, at least 39 of the 45 program units must be completed in residence at the Boston University Questrom School of Business. A maximum of 4 courses (12 of the 45 program units) may be waived based on previous completion of related graduate-level coursework.

For students who receive a waiver for a required course, an elective requirement may be substituted with a specific course requirement, therefore reducing or eliminating the number of elective choices a student may have. Final determination of any course waiver and applicable course substitution is made by the Program Faculty Director.

STEM Designation

The US Department of Homeland Security has designated the Master of Science in Mathematical Finance & Financial Technology program at the Questrom School of Business a STEM-eligible degree program. International students with F-1 student status may apply for a 24-month extension of their 12-month Optional Practical Training (OPT) employment authorization. More information about STEM OPT eligibility is available from the BU International Students & Scholars office (ISSO).

Admissions Information

Admission to the MSMFT program is competitive. Current application requirements and details can be found at Questrom’s Graduate Admissions office.