Identify, assess and manage the impact of innovative and disruptive technologies on the financial sector.
Develop the deep quant and tech skills that are in demand by corporations, consultants and government regulators in the financial sector.
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.
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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.
Semesters offered: Spring 2020
In this course, students will use financial econometric models to analyze problems of model specification, estimation, analysis and forecasting commonly faced by analysts in financial markets. The course materials cover the measurement and estimation of asset returns, earnings, macroeconomic data, risk and related applications in financial data analysis and visualization. Topics include regression analysis of time series/ARIMA models, multiple regression specifications and models of asset volatility including ARCH and GARCH. Throughout the course, students will use the statistical functions of the R programming language to analyze, model and forecast a variety of financial data.
Semesters offered: Fall 2020 | Spring 2020
This is a course about fixed-income securities and markets. It covers topics that are important for any MBA student that anticipates hedging interest rate exposures or otherwise transacting in the fixed-income market. The course reviews basic bond pricing concepts and important features of interest rate futures and options contracts. It also introduces a few (somewhat complicated) models of the term structure. This is a rigorous course that requires students to be familiar with basic investments and calculus concepts. While MGF633 is not a prerequisite for this course, students that are taking MGF633 simultaneously with the course will be better prepared. Like most finance courses, the course focuses more on lasting financial principles than on current institutional details.
Semesters offered: Spring 2020