Quantitative Finance Track

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

  • Focus on equity, bond and derivative markets in a curriculum built on advanced mathematics, finance and statistics.
  • Hone your skills in such topics as traditional CFA-relevant finance principles, quantitative methods, complex financial instruments and mathematical modeling using stochastic calculus.
  • Prepare for a wide variety of finance careers, from managing foreign-exchange risk for a multinational corporation, to designing complex corporate securities at an investment banking firm, to managing interest rate risk using derivatives at a major commercial bank.

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 undergraduate students may be able to complete the program in two semesters. All majors are welcome; however, business, math, economics and engineering majors are ideally suited to the program, provided you have the requisite calculus background.

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


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 636LEC Complex Financial Instruments

Students taking this course should expect to learn about financial derivatives. Among others, students will learn about how to price financial derivatives and how to incorporate various real-world frictions into binomial trees and stochastic processes (such as underlying the commonly used Black & Scholes model). In a case-study we will use R programming to replicate the risk-neutral price of a variance swap (underlying the so called Volatility Index or VIX). The course will be of particular interest for students who contemplate pursuing a career in the financial industry, e.g. as a Quantitative Analyst. The required prior courses depend on your trajectory (e.g., MGF 633 "Investment Management" or MGF 634 "Quantitative Methods in Finance"). Please consult your study guide for details. In general, students are expected to possess good knowledge of mathematics and statistics. Students should also feel comfortable with Excel and some basic programming knowledge will be helpful. Mathematical, statistical, and Excel skills required for this course will be reviewed during the course.

Credits: 3.00
Semesters offered: Spring 2018


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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