MQF

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The Robert H. Smith School of Business Master of Quantitative Finance (MQF) program leverages AI in preparing you to enter the evolving financial services industry. In this program, you’ll gain specialized knowledge of financial markets and institutions while further developing your coding and machine learning skills. Our MQF students are methodical problem solvers who are highly proficient in mathematics, coding and other quantitative subject areas.

$90k
Average starting salary
Top 20
Public college for high-paying jobs in finance, U.S. (Wall Street Journal, 2023)
3 to 4
Semesters to complete your degree

Why earn your Master of Quantitative Finance at Smith?

Smith’s STEM-designated MQF combines foundational knowledge of financial markets with rigorous coding and quantitative skills. Learn to apply math, probability, applied finance and coding within the financial services industry to develop strategies, manage risk and respond to rapid market changes. These skills can lead to careers in specialized fields like portfolio or derivatives management, algorithmic trading and financial engineering.

Manage Maryland’s Global Equity Fund

Manage a portion of the university’s endowment fund with your peers.

Use Cutting-Edge Technology

Gain access to cutting-edge analytics resources to refine your programming, data management and global investment skills.

Master AI for Finance

Discover how AI can help you more efficiently and effectively manage risk, analyze financial data and automate financial processes. Through Python coding, we'll teach you how machine-learning techniques can be applied.

For my experiential learning project, my team worked with data to develop models assessing housing risk in different markets. We looked at housing prices and general trends in the economy to create a housing risk index for each metropolitan statistical area. It was relevant to a real-world industry, and great to talk about at job interviews.

Iordan Koulav

Master of Quantitative Finance ’23

Advanced Skills You’ll Use

As an MQF student, you’ll lean into a wide range of concepts ideal for a career in corporate finance, risk management or asset management. You’ll put your quantitative skills to full use as you explore concepts and tools, such as:

Industry-Specific Tools and Skills:

  • AI in finance
  • Coding in Python
  • Financial data analytics
  • Financial programming
  • Risk modeling

Key Topics:

  • Computational finance
  • Financial engineering
  • Financial programming
  • FinTech
  • Institutional asset management
  • Machine Learning
  • Numerical methods and simulation
  • Portfolio management
  • Quantitative investment
  • Textual analysis
Smith Pioneers in Financial Modeling: The Kyle Model for market microstructure was created by Distinguished University Professor Albert "Pete" Kyle; The Variance Gamma Model for market share returns was created by Professor Emeritus Philip Madan; The Heston Stochastic Volatility Option Formula for underlying assets was created by Professor Steve Heston.

Download the curriculum map

Core Courses

Financial Management

2 credits | BUFN610

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.

Financial Data Analytics

2 credits | BUFN640

The course adopts a machine learning mindset to study standard techniques of econometric analysis of financial data. The focus is on understanding, interpretation, and practical applications in Python and Google Colab.

Machine Learning in Finance

2 credits | BUFN650

A hands-on course on applications of cutting-edge machine learning methods to financial modeling. It introduces students to a wide variety of machine learning techniques ranging from lasso regression to deep learning and TensorFlow.

Financial Mathematics

2 credits | BUFN670

Introduction to the mathematical models used in finance and economics with emphasis on pricing derivative instruments. Topics include elements from basic probability theory, distributions of stock returns, elementary stochastic calculus, Ito's Lemma, arbitrage pricing theory, and continuous time portfolio theory. Particular focus is on the financial applications of these mathematical concepts.

Advanced Capital Markets

2 credits | BUFN741

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.

Financial Programming

2 credits | BUFN745

This course introduces basic and innovative statistical modelling methods for financial markets, and equips students with analytical and programming tools for modelling and analyzing financial data. Examples of applications include portfolio management and risk management.

Valuation in Corporate Finance

2 credits | BUFN630

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, dicounted cash flow valuations, WACC and APV methods of valuation and Real Option Valuations.

Derivative Securities

2 credits | BUFN660

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.

Climate Finance Track

Climate Modeling and Analytic Tools
2 credits | Term C

An overview of the methodologies, assumptions and data used to develop climate models used for scenario and stress test analysis by financial services companies and other institutions. In addition to learning about the mechanics of climate models, their strengths and limitations, students will learn to how to use tools for conducting geospatial climate analytics. Financial and risk management modeling techniques including machine learning, statistical and simulation-based models for assessing climate change financial impacts will be examined in this course.

Carbon Accounting and Financial Disclosures
2 credits | Term C

A course surveying the accounting principles associated with climate and carbon disclosures. The course will explore the latest guidance from SEC and other regulatory organizations on financial disclosures including The Task Force on Climate-Related Financial Disclosures (TCFD).

Experiential Learning Project
2 credits | Term D

A course where small student teams led by a faculty advisor work with a corporate or governmental sponsor on an applied problem of interest relating to climate finance and risk management. Students would learn how to work in an interdisciplinary team to conduct analysis on some applied climate finance or risk business problem leveraging concepts and tools from the other courses in the climate finance track.

Portfolio Analysis, Investment Strategies and Climate
2 credits | Term D

In this course, students will learn important techniques used by asset managers, hedge funds and private equity for valuing various types of assets and companies based on their exposure to climate-related risks. Other financial tools such as green bonds and associated financing vehicles will also be presented for evaluation.

General Elective Courses

Entrepreneurial Finance and Private Equity

2 credits | BUFN717

Prerequisite: Corporate Finance

An advanced topics course in Corporate Finance. The major emphasis is how financiers help growing firms - and in particular young start-ups - using different types of securities at different points in the industry's and firm's life. Financing arrangements and securities studied will include private equity funds and private financings placements, Venture Capital (VC) and preferred equity, Investment Banks through Initial Public Offerings (IPOs), Private equity finds, debt and leveraged buyouts. Students will learn additional techniques that will help them understand how financiers value firms and how to understand, plan and value different financing strategies.

International Investment

2 credits | BUFN721

Addresses international stock markets, portfolio theory, international interest rates, exchange rates and exchange rate derivatives (options, forwards, and futures), exchange rate swaps and exchange rate exposure (operating, translation, and transaction), foreign investment strategy.

Bank Management

2 credits | BUFN724

Fixed Income Analysis

2 credits | BUFN732

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.

Portfolio Management

2 credits | BUFN734

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.

Fixed Income Derivatives

2 credits | BUFN744

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.

Financial Engineering

2 credits | BUFN742

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.

Financial Risk Management

2 credits | BUFN747

This course surveys risks and techniques associated with asset-liability and nonfinancial risks including market and interest rate risk, liquidity risk, operational risk and model risk, among others. Techniques such as portfolio value-at-risk (VaR) are used in realistic empirical examples to illustrate the methods. Key rate duration, principal components analysis and analytical and simulation-based VaR techniques are used to estimate interest rate risk exposure for financial firms. Hedging these risks using various financial derivative products such as options, swaps and futures contracts is explored. Operational risk is estimated leveraging Poisson loss distributions and model risk and validation techniques are reviewed.

Institutional Asset Management

2 credits | BUFN726

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.

Asset-Liability and Non Financial Risk Management

2 credits | BUFN747

This course surveys risks and techniques associated with asset-liability and nonfinancial risks including market and interest rate risk, liquidity risk, operational risk and model risk, among others. Techniques such as portfolio value-at-risk (VaR) are used in realistic empirical examples to illustrate the methods. Key rate duration, principal components analysis and analytical and simulation-based VaR techniques are used to estimate interest rate risk exposure for financial firms. Hedging these risks using various financial derivative products such as options, swaps and futures contracts is explored. Operational risk is estimated leveraging Poisson loss distributions and model risk and validation techniques are reviewed.

Market Microstructure

2 credits | BUFN758X

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, transaction 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 transaction data.

Who Has Hired MQF Grads