Master of Quantitative Finance Overview

Our Master of Quantitative Finance (MQF) program addresses a growing need for professionals with sophisticated quantitative, computational, and financial modeling skills.  The MQF prepares you for a wide range of careers in finance: modeling and managing risk; trading; financial engineering; securities pricing; portfolio management; tactical asset allocation; and financial market regulation.

Our MQF degree is STEM-qualified. We offer students cutting-edge quantitative and programming skills plus unique domain expertise in financial institutions, markets and decisions in all major asset classes, including equity, fixed income, derivatives, and FX markets.

The MQF requires 36 credit hours and comprises core courses and 20+ credits of electives. The core courses provide solid fundamentals in economic, statistical and mathematical models relevant to the finance industry. A flexible set of electives let students become specialists within their chosen career paths. Some students undertake ELPs (experiential learning projects) with industry partners.

The MQF degree can be finished in one to two years. Many students prefer the 2-year period to explore internship opportunities or ELPs with high-profile industry partners. 

Modern methods of computational statistics and their application to both practical problems and research. S-Plus and SAS programming with an emphasis on S-Plus. S-Plus objects and functions, and SAS procedures. Topics include data management and graphics, Monte Carlo and simulation, bootstrapping, numerical optimization in statistics, linear and generalized linear models, nonparametric regression, time series analysis.

Required Courses

Elective Courses

Required Courses

BUFN610: Financial Management
Credits: 2

Focuses on the valuation of the real assets of firms as well as the valuation of stocks and bonds, the primary financial assets in an economy. While details vary, the conceptual foundations of valuation boil down to three themes: time value of money, no-arbitrage, and systematic risk.

BUFN630: Valuation in Corporate Finance
Credits: 2

An advanced topics course in Corporate Finance dealing with valuation. Main topics will be, building pro forma statements, cost of capital, using ratios and comparables to value projects and firms, discounted cash flow valuations, WACC and APV methods of valuation and Real Option Valuation.

BUFN640: Financial Data Analytics (previously Financial Econometrics I)
Credits: 2

In this course, we study standard techniques used in the econometric analysis of financial data and discuss the underlying techniques and focus on understanding and interpretation.

BUFN650: Machine Learning in Finance (previously Financial Econometrics II)
Credits: 2

A hands-on and application-oriented short course on data management and financial modeling. It introduces students to basic data management techniques and a variety of analytical models used in finance.

BUFN660: Derivative Securities
Credits: 2

Standard types of derivatives contracts are presented and illustrated as to how they are used in practice. The theory of pricing these contracts is then presented in detail. The use of static and dynamic replication strategies and the concept of no-arbitrage strategies is illustrated in numerous ways. Standard valuation techniques are covered, and standard formulas are presented. The theory is then applied to develop specific pricing and hedging strategies for various types of derivatives on different underlying assets. The management of the exposure of various risks is covered in detail as well.

BUFN670: Financial Mathematics
Credits: 2

We will cover basic concepts in discrete-time and continuous time finance, including stochastic calculus and treatment of jumps, conditional expectations, Feynman-Kac theorem, Girsanov theorem, risk-neutral pricing of derivatives (forwards, futures, bonds, options), convex optimization. The focus is on financial models, applications, and implementation.

BUFN741: Advanced Capital Markets
Credits: 2

This course covers modern theories and techniques for investments and asset pricing. The main topics covered are portfolio theory, pricing models, market efficiency, fixed income investment, forwards and futures, and options.

BUFN745: Financial Programming
Credits: 2

Deepens the programming and computing skills necessary in the finance profession, especially for quantitative roles involving big data and modeling. The course aims to familiarize students with large scale financial data and to further develop practical analytical tools.

Elective Courses 

BUFN726: Institutional Asset Management
Credits: 2

Examines how money is managed by organizations such as university endowments, pension funds, mutual funds, hedge funds, and private equity funds. Involves a mixture of finance and economics and emphasizes the incentives professional money managers face within the context of the organizational structure in which they operate. Particular attention is paid to compensation structures and monitoring mechanisms.

BUFN732: Fixed Income Analysis
Credits: 2

Describes important financial instruments which have market values that are sensitive to interest rate movements. Develops tools to analyze interest rate sensitivity and value fixed income securities. Defines and explains the vocabulary of the bond management business.

BUFN734: Portfolio Risk Management
Credits: 2

Provides training that is important in understanding the investment process—the buy side of the financial world. Specifically, the objective is to provide graduate-level instruction in the following topics, both in theory and in using financial markets data to test the basic theory and practice of portfolio choice and equilibrium pricing models and their implications for efficient portfolios.

BUFN736: Quantitative Investment Strategies
Credits: 2

Provides an introduction to quantitative techniques of selecting equities, as used commonly among long-short equity hedge funds and other quantitative equity asset management companies. Statistical factor models are developed to locate stocks with higher expected returns, based on the observable characteristics of the stocks. Implementation issues, including statistical estimation, backtesting and portfolio construction, are covered, as is performance evaluation.

BUFN742: Financial Engineering
Credits: 2

Introduces and applies various computational techniques useful in the management of equity and fixed income portfolios and the valuation of financial derivatives and fixed income securities. Techniques include Monte Carlo Simulation and binomial/lattice pricing models. Emphasis is on bridging theory with the design of algorithms and models that can be directly applied in practice.

BUFN744: Fixed Income Derivatives
Credits: 2

Surveys fixed-income assets and related securities such as Exchange-traded bond options; bonds with embedded options; floating rate notes; caps, collars, and floors; floating rate notes with embedded options. Also, surveys advanced tools for interest-rate and fixed-income portfolio management, including the use of derivative securities, and the application of binomial trees for analysis of options, and a sound understanding of stochastic yield curves.

BUFN758A: Text Mining for Economics and Finance
Credits: 2

Informs students about recent text-mining techniques to process and analyze "text data" (newspapers, central bank transcripts, stock tweets, etc.) for financial questions. This course will familiarize students on a broad level with pre-processing techniques, dictionary methods, naïve Bayes classification, topic models, word vectors, the statistical background of these techniques as well as applications of these tools in recent financial academic studies. 

BUFN758D: Big Data in Finance
Credits: 2

Provides a deep understanding of the many ways big data is altering the financial landscape. This course follows a stylized data life-cycle, from data acquisition to end-user deployment, illustrating some of the new tools that are brought to bear, with a focus on big data engineering. The course will emphasize formal concepts and approaches to critical financial challenges.

BUFN758L: FinTech
Credits: 2

Provides an introduction to both the ‘Fin’ and the ‘Tech’ part of FinTech. This course focuses on understanding the evolution of ‘traditional’ finance methods—namely the disruptions and innovations that have transformed: (i) how we raise capital; (ii) how we invest or manage capital; (iii) how we transact and transfer capital; and (iv) how we monitor and maintain the integrity of financial institutions and transactions. This course provides a foundation in the basic concepts and frameworks that underlie these innovations and their applications.

BUFN758M: Hedge Fund Management
Credits: 2

Gives students a greater understanding of how public market alternative asset management firms operate. Provides an overview of the operational structure of a hedge fund. A great deal of time will be spent on understanding and implementing the tools that hedge funds use, such as volatility, shorting, pairs trades, long equity, commodity and fixed income investing. By the end of the class, students should be able to construct hedged portfolios. 

BUFN58X: Market Microstructure
Credits: 2

The course examines—from theoretical, institutional, and empirical perspectives—how prices in speculative markets are determined by the interaction of traders. Topics covered include market making, informed trading strategies, liquidity, bid-ask spreads, transactions costs, market impact, price manipulation, and high-frequency trading. The course examines markets for equities, bonds, commodities, and foreign exchange. There are several empirical exercises using transactions data.

Global Equity Fund

This limited-enrollment (by application) fund provides students with the opportunity to apply the skills learned in finance classes to actual investment decisions through management of an investment fund.

Experiential Learning Projects

These limited-enrollment (by application) projects vary from semester to semester and provide hands-on experiential learning and actual business cases.