Degree: Master of Finance (MFin)
Program Overview
The Master of Finance program trains students to make immediate and skilled contributions in the constantly changing marketplace of finance. Through case studies, financial big data projects, real-life projects under corporate executives, corporate presentations, field trips, and internships, the Master of Finance students acquire a rigorous foundation in finance while applying key concepts, theories, and analytical techniques in and out of class. Five tracks of specialization are offered—Corporate Finance, Corporate Financial Analytics, Risk Management Analytics, Financial Big Data Analytics, and FinTech. The Master of Finance program has been accepted into the CFA Institute University Recognition Program. Four of the tracks are also STEM accredited. In addition to the resources offered by Weatherhead School’s Career Management Office, the Master of Finance program has a dedicated executive director to provide students experiential learning, and to assist them in internships and placements, and help build relationships. There are regular corporate and city treks, practitioner seminars, academic seminars, and networking events.
For more information visit the Master of Finance program's website or contact Marybeth Keeler, Associate Director, at 216.368.3688.
Learning Outcomes
- Students are competent analytical problem solvers.
- Students are skilled at solving unstructured problems.
- Students demonstrate effective teamwork.
Program Requirements
The Master of Finance degree curriculum offers students the flexibility of determining the structure of their program based on their long-term goals and specific areas of interest. Students can graduate with the basic program of 30 credit hours in two semesters, or work toward additional departmental certification, available upon successful completion of 39 credit hours in three or four semesters. The Master of Finance program offers five specializations for students to build their own future, four of which are STEM accredited.
The curriculum is comprised of the following components:
Course List Code | Title | Credit Hours |
FNCE 401 | Financial Orientation b | 1.5 |
FNCE 404 | Financial Modeling | 3 |
FNCE 421 | Corporate Financial Analysis | 3 |
FNCE 429 | Investment Management | 3 |
FNCE 430 | Derivatives and Risk Management | 3 |
FNCE 435 | Empirical Finance | 3 |
FNCE 436A | Individual, Team and Career Development | .75 |
FNCE 436B | Individual, Team and Career Development | .75 |
Total Credit Hours | 18 |
Specializations
Specialization courses develop expertise in a particular specialization: Corporate Financial Analytics, Corporate Finance, Risk Management Analytics, Financial Big Data Analytics, or FinTech. Enrollment in elective courses may be contingent upon appropriate performance in the program. Students enrolled in the 30 credit hour plan will take 12 credit hours in a specialization. Students enrolled in the 39 credit hour plan will take 21 credit hours in a specialization.
Corporate Financial Analytics Specialization (STEM Eligible)b
Course List Code | Title | Credit Hours |
FNCE 414 | Banking and RegTech | 3 |
FNCE 428 | Financial Strategy and Value Creation | 3 |
FNCE 432 | Corporate Risk Management | 3 |
FNCE 434 | Financial Analytics and Banking | 3 |
or FNCE 440 | Financial Decisions Modeling and Analytics |
FNCE 470 | Financial Models Using Big Data | 3 |
FNCE 480 | Global Banking & Capital Markets | 3 |
FNCE 491 | Python Programming w Appl in Finance | 3 |
Total Credit Hours | 21 |
Corporate Finance Specializationb
Course List Code | Title | Credit Hours |
FNCE 403 | Corporate Financial Technology a | 3 |
FNCE 428 | Financial Strategy and Value Creation a | 3 |
FNCE 440 | Financial Decisions Modeling and Analytics | 3 |
FNCE 450 | Mergers and Acquisitions | 3 |
FNCE 480 | Global Banking & Capital Markets a | 3 |
c | 6 |
Total Credit Hours | 21 |
Risk Management Analytics Specialization (STEM Eligible)b
Course List Code | Title | Credit Hours |
FNCE 412 | Algorithmic Trading | 3 |
FNCE 431 | Fixed Income Markets and Their Derivatives | 3 |
FNCE 432 | Corporate Risk Management | 3 |
FNCE 433 | Quantitative Risk Modeling | 3 |
FNCE 434 | Financial Analytics and Banking | 3 |
or FNCE 440 | Financial Decisions Modeling and Analytics |
FNCE 460 | Investment Strategies | 3 |
FNCE 491 | Python Programming w Appl in Finance | 3 |
Total Credit Hours | 21 |
Financial Big Data Analytics Specialization (STEM Eligible)b
Course List Code | Title | Credit Hours |
FNCE 412 | Algorithmic Trading | 3 |
FNCE 431 | Fixed Income Markets and Their Derivatives | 3 |
FNCE 433 | Quantitative Risk Modeling | 3 |
FNCE 460 | Investment Strategies | 3 |
FNCE 470 | Financial Models Using Big Data | 3 |
FNCE 471 | Applications in Financial Big Data | 3 |
FNCE 493 | Blockchains, Cryptocurrencies, and Cryptoventures | 3 |
Total Credit Hours | 21 |
FinTech Specialization (STEM Eligible)b
Course List Code | Title | Credit Hours |
FNCE 403 | Corporate Financial Technology | 3 |
FNCE 412 | Algorithmic Trading | 3 |
FNCE 414 | Banking and RegTech | 3 |
FNCE 460 | Investment Strategies | 3 |
FNCE 493 | Blockchains, Cryptocurrencies, and Cryptoventures | 3 |
FNCE 494 | Artificial Intelligence for Financial Modeling | 3 |
c | 3 |
Total Credit Hours | 21 |