Rigorous coursework to prepare students for careers in industry and academia.

Classes are more analytical and quantitatively focused than traditional MS programs in either Economics or Finance. MS-Financial Economics (MSFE) students are highly sought after for their specialized training in econometrics and financial applications.

Faculty have created cutting edge courses that provide students with in demand analytical skills unique to the world of finance.

“The typical MBA degree in finance should be repurposed and replaced with a more challenging curriculum that blends engineering, computer science, finance and economics into a tool kit for practitioners that seek to work on the edge of the frontier of knowledge. The MSFE does exactly this and thereby provides a pool of talent that is extremely valuable in the areas of multi-asset risk management, capital structure arbitrage, portfolio optimization, and valuation.”

David Villa, Executive Director & Chief Investment Officer, State of Wisconsin Investment Board

MSFE Curriculum

The core of the MSFE Program is eight courses in economics and finance. In addition to the core courses, MSFE students will also take a minimum of two electives of their choosing.

The required core courses and electives are listed below.

Students will take the following eight core courses.

Core required courses: 

FIN 720: Investment Theory and Practice 3 credits

FIN 725: Corporation Finance – Theory and Practice 3 credits

FIN 730: Derivative Securities – Theory and Practice 3 credits

FIN 830: Advanced Derivative and Fixed-Income Securities 3 credits

ECON 702: Macroeconomics I 3 credits

ECON 704: Econometrics I 3 credits

ECON 721: Financial Microeconomics 3 credits

ECON 724: Financial Econometrics 3 credits

Students will select 6 credits of electives from the below approved list.  Three elective credits must be from Economics and three elective credits must be from Finance. For additional information on elective courses, please see the UW Guide:


FIN 650: Mergers and Acquisitions 3 credits

FIN 765: Contemporary Topics 3 credits

ECON 709: Economic Statistics and Econometrics I 3 credits

ECON 711: Economics Theory – Microeconomics Sequence 3 credits

ECON 712: Economic Theory – Macroeconomics Sequence 3 credits

ECON 725: Machine Learning for Economists 3 credits

ECON 730: International Financial Economics 3 credits

ECON 770: Data Analytics for Economists 3 credits

Total Credits:  30 credits

More information on Required Core Courses

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FIN 720: Investment Theory and Practice

Topics include:

  • Structure and securities market functioning
  • Principles of portfolio construction
  • Models of the trade off between risk and expected return

FIN 725: Corporation Finance – Theory and Practice

Topics include:

  • Techniques of capital budgeting under certainty and uncertainty
  • Valuation of projects and firms
  • Theory of capital structure
  • Dividend policy and cost of capital

FIN 730: Derivative Securities – Theory and Practice

Topics include:

  • Pricing and uses of the most common derivative contracts
  • Trading and management of portfolios
  • Advanced mathematical and statistical financial analyses

FIN 830: Advanced Derivative and Fixed-Income Securities

Topics include:

  • Introduction to continuous time finance models
  • Black-Scholes and stochastic volatility models
  • Term structure modeling of interest rate derivatives
  • Price derivatives using numerical methods
  • Applications and hands on programming

ECON 702: Macroeconomics I

For additional information, please see the UW Guide:

ECON 704: Econometrics I

Topics include:

  • Econometric methods, theory, and applications
  • Linear regression, least-squares estimation, inference, and hypothesis testing

ECON 721: Financial Microeconomics

Topics include:

  • Programming Pricing Algorithms
  • Hands-on Training in Python
  • Pricing Fixed-Income Assets (bonds, mortgages) from YTM
  • Stochastic Discount Factor Methods
  • Modeling Default Risks and Systemic Risks

ECON 724: Financial Econometrics

Topics include:

  • Empirical asset returns, capital asset pricing, portfolio allocation
  • Linear ARMA & vector autoregressive modeling for estimation and forecasting
  • ARCH & stochastic volatility modeling
  • Machine learning and big data

Useful Links

Please visit UW’s Course Search and Enroll for an online listing of courses offered in recent terms.

For a full list of courses offered at UW-Madison, please see the course listing in the Guide: