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). The 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 MF 610 Mathematical Finance Career Management (1 unit, taken each term for a total of 3 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 (3 units)**

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 FinTech Programming
• QST MF 815 Advanced Machine Learning Applications for Finance
• QST MF 821 Algorithmic and High-Frequency Trading
• QST MF 840 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.

*Because of the integrated structure of the curriculum and course rigor, all students must remain on the prescribed curriculum of 13 units per term. Any additional courses beyond the 13-units-per-term curriculum must be approved in advance by the Program Executive Director.

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

Electives

• QST AC 860 Accounting for Risk and Portfolio Management
• QST MF 728 Fixed Income Securities
• 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
• QST MF 810 FinTech Programming
• 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 Financial Econometrics
• QST MF 850 Deep Learning and Statistical Learning
• QST FE 920 Advanced Capital Markets
• QST MF 921 Advanced Topics in Asset Pricing

All Mathematical Finance & Financial Technology courses are taken for 3 units. Students must pick elective courses from the approved list of courses. 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 Executive Director in consultation with the Mathematical Finance & Financial Technology Program Development Committee (PDC).

Academic Standards

Academic Performance Review for MS in Mathematical Finance & Financial Technology Students

The Specialty Master’s & PhD Center monitors students’ academic performance at the end of the fall and spring terms, up until the time of graduation. A student must maintain a cumulative grade point average (CGPA) of at least 2.70 (on a 4.0 scale) to be in good academic standing (i.e., 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.

The Mathematical Finance & Financial Technology Faculty Program Development Committee (PDC) has final responsibility for decisions regarding students with poor academic performance. The committee determines whether students will be permitted to stay in the program, and if so, what specific steps must be taken to regain good academic standing. A PDC decision for permanent academic withdrawal is final and no appeals to the PDC beyond the Student Statement (described below) are allowed.

Students with a CGPA below 2.70 after the fall and spring terms will be referred to the PDC for review. Students will be informed of their academic position via their BU email address prior to the start of the subsequent term. All students in poor academic standing must meet with their Specialty Master’s & PhD Center advisor (in person or by telephone) within 48 hours of receipt of this communication to discuss the situation. If a Student Statement is submitted, this is due within 72 hours of the performance notification. It is the student’s responsibility to be aware of the tight window between notice and action and to plan accordingly.

After 13 units attempted, Mathematical Finance & Financial Technology students with a CGPA less than 2.30 will be withdrawn from the program. Students with a CGPA between 2.3 and 2.69 after 13 units may be academically withdrawn from the program or receive a written warning with recommendations for improvement.

After 24 units attempted, students with a CGPA less than 2.30 will be automatically withdrawn from the program. Students with a CGPA between 2.3 and 2.69 after 24 units may be academically withdrawn from the program or receive a written warning with recommendations for improvement. Mathematical Finance & Financial Technology students are not permitted to take additional units, beyond the term in which they have completed their degree requirements, to improve their CGPA.

After all program units are completed, all students must achieve a 2.70 or higher CGPA in order to graduate. Students are not permitted to take additional units beyond the term in which they have completed their degree requirements in order to improve their CGPA or restart enrollment, nor can they withdraw and re-enroll.

Please be aware that your CGPA can also affect your eligibility for continuing financial aid, including scholarships and loans. Students with a CGPA below 3.3 will be at risk of losing their scholarship.

Student Statement

The Student Statement is voluntary, though it is strongly encouraged, as it offers the sole opportunity for student input into PDC decisions. The statement is self-reflective and provides the student’s explanation for their poor academic performance. The statement is due within 72 hours of notice of poor performance by the Specialty Master’s & PhD Center. The statement is the student’s individual work product and must be prepared accordingly.

Degree Completion

Upon successful completion of program requirements, Mathematical Finance & Financial Technology students are expected to graduate in January. All students who graduate in January are invited to attend the Questrom School of Business commencement ceremony in the following May.

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 51 program units must be completed in residence at the Boston University Questrom School of Business. A maximum of 4 courses (12 of the 51 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.