Financial Risk Management Track

Are you ready for the next step in your finance career?

  • Immerse yourself in a rigorous introduction to risk diversification and measurement, portfolio theory, statistics, programming finance models in statistical software and Excel skills.
  • Apply your knowledge to such topics as foreign currency trading and risk, interest and inflation rate models and hedging strategies. You’ll also perform statistical analysis using big data, learn about investments, financial derivatives, fixed income securities and financial institutions.
  • Take courses in corporate finance, financial modeling, programming and independent research. You can even take graduate courses outside the Finance Department to complete a customized program that fits your interests.
  • Prepare for the CFA exam with a curriculum that matches the topics on the exams, to help you prepare for that career-differentiating certification.

Contact Us

Graduate Programs Office
School of Management
University at Buffalo
203 Alfiero Center
Buffalo, NY 14260-4010

Tel:  716-645-3204
Fax: 716-645-2341
som-apps@buffalo.edu
Meet our Team

The MS Finance is a STEM (science, technology, engineering and mathematics) curriculum with 36 credits typically completed in three semesters. Some students extend to a fourth semester, and UB undergraduates may be able to complete the program in two semesters. All majors are welcome to apply; however, business, math, economics and engineering majors are ideally suited to the program.

Curriculum

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Fall Start

MGF 696LEC Portfolio Theory and Strategy

The course covers sophisticated approaches to investing and it has an introduction and three main parts. The introduction covers measures of performance and risk and methods to calculate them in closed form or from historical data. The first part of the course covers investment strategies across several asset classes, from traditional ones such as value or growth investing to strategies employed by hedge funds, such as arbitrage, option trading and other quant strategies. The second part of the course addresses portfolio construction, from assessing a utility function to the investor to constructing an optimal portfolio maximizing that utility. Investor types covered are individuals saving for retirement, speculators, university endowments or foundations, or pension funds. Finally, the last part of the course addresses the topic of risk measurement and management, with an emphasis of risks faced by decentralized organizations, such as funds of funds, foundations, or pension funds.

Credits: 3.00
Semesters offered: Fall 2018
Co-Requisite: MGF 633


STEM or Non-STEM Elective (select two)

Capstone Course (select one):

MGF 644LAB Supervised Research - Fixed Income

Students will learn to conduct empirical research on fixed-income securities. The initial learning process involves a limited number of lectures on fixed-income pricing theory, followed by formal training on how to access data from fixed-income database(s). Using the above resources students will also build an investment portfolio for a given risk level. Students will then develop testable hypotheses that employ mathematical modeling, and develop and apply statistical analyses to data to test the hypotheses. Finally, students will develop and present a professional research report based on the empirical findings.

Credits: 3.00
Semesters offered: Fall 2018


MGF 645LAB Supervised Research - Equities

Students will learn to conduct empirical research on equities. The initial learning process involves a limited number of lectures on asset-pricing pricing theory, followed by formal training on how to access data from equity-related database(s). Students with then develop testable hypotheses that employ mathematical modeling, and develop and apply statistical analyses to data to test the hypotheses. Finally, students will develop and present a professional research report based on the empirical findings.

Credits: 3.00
Semesters offered: Fall 2018 | Spring 2018


Spring Start

MGF 635LEC Financial Derivatives

Objectives of this technical course include providing students with knowledge of specific trading mechanics, basic economic concepts and technical asset valuation tools to successfully employ a wide variety of derivative securities into a risk management context; as well as to understand risk-return tradeoffs associated with specialized speculative strategies in derivatives markets. A broad survey of rapidly-changing forward, futures, options, swaps (and other related derivative types) is followed by emphasis upon asset pricing models of complex financial instruments using both classical economic theory and advanced mathematical techniques. Basic knowledge of differential calculus is expected. Basics of stochastic calculus will be covered. Students will be prepared to employ material learned into a corporate (or smaller firm) environment for management of business-related risk from fluctuating commodity prices, interest rates changes, foreign exchange fluctuations and construction of stock/bond investment fund 'portfolio insurance'.

Credits: 3.00
Semesters offered: Fall 2018 | Spring 2018
Co-Requisite: MGF 633 or MS Accounting Majors.


STEM or Non-STEM Elective (select two)

Capstone Course:

MGF 644LAB Supervised Research - Fixed Income

Students will learn to conduct empirical research on fixed-income securities. The initial learning process involves a limited number of lectures on fixed-income pricing theory, followed by formal training on how to access data from fixed-income database(s). Using the above resources students will also build an investment portfolio for a given risk level. Students will then develop testable hypotheses that employ mathematical modeling, and develop and apply statistical analyses to data to test the hypotheses. Finally, students will develop and present a professional research report based on the empirical findings.

Credits: 3.00
Semesters offered: Fall 2018


MGF 645LAB Supervised Research - Equities

Students will learn to conduct empirical research on equities. The initial learning process involves a limited number of lectures on asset-pricing pricing theory, followed by formal training on how to access data from equity-related database(s). Students with then develop testable hypotheses that employ mathematical modeling, and develop and apply statistical analyses to data to test the hypotheses. Finally, students will develop and present a professional research report based on the empirical findings.

Credits: 3.00
Semesters offered: Fall 2018 | Spring 2018


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