Essential Education, Focused on the Future
Designed for recent graduates and early-career professionals, the MS in Finance curriculum marries the essentials of education in finance theory with the quantitative and computational skills now driving the field, along with intensive practical application throughout.
Start Date: Early July (Summer Semester)
Duration: 12 or 16 months, full-time; 39 credits
Location: On-campus; classes held during the day
- Rigorous, 39-credit, STEM-designated curriculum
- CFA affiliation, ensuring classes prepare students for the CFA exam (optional)
- Technical skill-building courses: Intro to Python Programming, Computing for Finance, Machine Learning for Finance, Cryptocurrency, Blockchain & Their Business Applications
- Use of programming languages, software, and databases: Python, MATLAB, Stata, Excel VBA, ModelRisk, Bloomberg, Factset, CRSP, Compustat, among others
- Intensive experiential learning component analyzing real financial challenges for real client companies
Program Structure: Graduate in 12 or 16 Months
MSF students may elect to complete the program in 12 or 16 months based on personal goals and preferences. Students have until the end of the first semester of the program to choose their track, leaving time to consult with their career coach and academic advisor before deciding.
- Default curriculum option
- Finish the program in one calendar year
- Return to full-time job market quickly
- Ideal for students with previous internship and/or full-time work experience in finance
- Additional summer and fall semester at no extra tuition cost
- Option to spread out class schedule
- Flexibility for summer finance internship
- Internship assistance from Graduate Business Career Center
- Recommended for those joining directly after undergrad studies, pivoting from another career area, or who would like to further boost their resumes before graduation
MSF 6421: Computing for Finance (2 credits)
This course first introduces students to specific software (e.g., Excel VBA, ModelRisk Monte Carlo simulator) and databases (e.g., Bloomberg, Factset, CRSP, Compustat) that will be used throughout the MS program. It then focuses on the use of Excel for many topics in finance, including modern portfolio theory, optimal portfolio analysis and binomial option pricing. This course often takes the material being learned in the "Fundamentals of Finance" course to motivate specific examples.
MSF 6221: Fundamentals of Finance I (2 credits)
This course is the first course in a three-course sequence to introduce the ideas of corporate finance. This course focuses on an overview of corporate finance in the firm, the valuation principle, the time value of money, interest rates, valuing bonds, risk and return, and estimating the cost of capital.
MSF 6031: Financial Accounting (3 credits)
This course provides students with a deep understanding of financial accounting fundamentals so that they can make decisions based on reported financials. Students will learn how a firm's operating activities, investments, and financing transactions are recorded in the income statement, balance sheet, and statement of cash flows. Students will develop some skills needed to analyze financial statements that would later be used.
MSF 6920: Introduction to Python (2 credits)
This course is focused on analyzing economic and financial data using Python. You will learn how to access powerful and popular libraries for data access, analysis, and visualization. Most of class time will be spent completing practical, hands-on exercises.
MSF 6422: Financial Econometrics & Computational Methods I (2 credits)
This course provides an introduction to the methods used in empirical finance. A review of statistics is followed by intensive instruction on matrix algebra that culminates in a fundamental understanding of linear regression, the basic empirical tool. Asset pricing theories are discussed and developed and then methods are derived to test them. The course emphasizes estimation and inference using computer-based applications.
MSF 6222: Fundamentals of Finance II (2 credits)
Section I of this course introduces capital budgeting. Students use the cost of capital learned at the end of the first course in conjunction with an introduction to the calculation of cash flows and the use of decision rules for project selection. Section II moves into stock valuation and company valuation based upon the dividend discount model and enterprise model of valuation; students are also exposed to other valuation methods. Section III introduces the effect of capital structure on company valuation, starting with perfect markets and introducing the opposing effects of taxation and financial distress on valuation. Students complete a case to demonstrate understanding of the core concepts from the first three sections; the case is a continuing case with each week building on the prior week’s work. Section IV provides an introduction to financial options and option valuation.
MSF 6322: Corporate Valuation & Modeling (2 credits)
This course develops the financial modeling principles and tools needed to build, operate, and understand the standard business performance, M&A, equity, and credit models that have become central to modern financial decision making. The course develops a deep understanding of financial models so they can be used to analyze a wide range of financial issues. Finance concepts introduced in other courses are reinforced by having students build them into models and by having students interpret the results produced by those models. Students build a financial model on their own, learn to use a fully developed financial model, and use models repeatedly to evaluate and plan performance, to estimate value added from projects, operating strategies and financing proposals, and to estimate the value of securities. This course extensively uses VBA macros, sensitivity tables, and scenario analyses.
MSF 6423: Financial Econometrics & Computational Methods II (2 credits)
This course builds on Financial Econometrics I and provides instruction on the econometrics used in empirical finance. Topics include time series analysis, parametric models of volatility, evaluation of asset pricing theories, and models for risk management. The course emphasizes estimation and inference using computer-based applications.
MSF 6321: Quantitative Portfolio Analysis (2 credits)
This course develops and examines models for portfolio decisions by investors and the pricing of securities in capital markets. Students develop portfolio theory along the way and also study the extensive empirical work that characterizes movements in security prices and evaluates alternative asset pricing models. Topics include the mean variance portfolio analysis, the capital asset pricing model, arbitrage pricing theory, the empirical performance of asset pricing model (market anomalies), multi-factor asset pricing models, time varying risk and returns, and portfolio performance evaluation, including style and attribution analysis. Extensive use of the computer is required.
MSF 6223: Fundamentals of Finance III (2 credits)
This course focuses on the three major decisions of a firm: the financing decision, the capital structure decision, and the payout decision. There is also an introduction to corporate valuation. This course uses a balanced mix of lectures and case studies, and emphasizes the use of real world data.
MSF 6121: Fixed Income & Securities Analysis (2 credits)
This class provides an introduction to fixed income markets. Topics include the price/yield relation, no-arbitrage pricing of stripped coupon bonds, the duration/convexity approximation, the term structure of interest rates, defaultable bonds, mortgage-backed securities, inflation protected securities, bonds with embedded options, swap rates, the Fed Funds rate, repurchase agreements, and attribution analysis.
MSF 6522: Derivatives & Risk Management I (2 credits)
This class provides an introduction to derivatives markets. This course is designed to achieve two main objectives. First, provide students with a rigorous framework used in valuing derivative contracts. This includes an in-depth treatment on the two work horses of the binomial model and the Black-Sholes-Merton model. Second, apply the framework to understand a wide variety of issues related to risk management and investment decisions.
MSF 6621: Finance within the Macroeconomy (2 credits)
This course provides students with an understanding of modern macroeconomics, with a particular interest in how financial markets and institutions fit into the overall macro system. Students gain a much stronger sense of the ongoing macroeconomic news and policy discussion. Having a sense of this material is often helpful in job interviews as well.
MSF 6821: Experiential Learning (2 credits)
This course is the first half of the experiential learning segment of this program. Students are partitioned into small groups to investigate a particular project with a client company. Students identify the most crucial issues associated with the project, collect the necessary data that will be used to analyze the issue at hand, and determine the quantitative tools that will be required to analyze the relevant issues.
Electives (2 credits)
See example elective courses below.
MSF 6424: Intro to Machine Learning for Finance (2 credits)
Machine learning methods are now widely used in finance. This class covers fundamental methods, with particular attention devoted to the use in asset pricing and credit assessment. A real project has several steps: 1) data collection, 2) data management, 3) exploratory data analysis, 4) learning and predicting, 5) communicating results. The lectures focus on techniques for step 4. The homework provides hands-on practice including the other steps.
MSF 6021: Communications for Finance (2 credits)
This course covers guidelines and practical skill development for writing well-organized, professional documents and delivering confident, credible, and dynamic presentations. Students will practice designing and delivering effective messages including reader-friendly documents and PowerPoint using a professional writing style and document design. Through discussion and practice, students will also learn to deliver poised, formal, and informal presentations to small and large groups both individually and in teams.
MSF 6821: Experiential Learning (2 credits)
This course is the second half of the experiential learning segment of this program. Student groups continue to work with their clients to analyze the financial issue at hand using quantitative tools learned throughout the program. At the end of the course, students present their findings and pitch business solutions to their clients, for the companies to utilize moving forward.
Visit our MSF Experiential Learning webpage for more information about our students' high-impact client work.
Electives (2 credits)
See example elective courses below.
- FINA 6125 Cryptocurrency, Blockchain, and their Business Applications (2 credits)
- FINA 6123 Financial Services Industry (2 credits)
- FINA 6222 Mergers and Acquisitions (2 credits)
- FINA 6324 Securitization Markets (2 credits)
- FINA 6325 Behavioral Finance (2 credits)
- FINA 6621 International Financial Management (2 credits)
- FINA 6529 Advanced Topics in Fixed Income and Derivatives (2 credits)
- Graduate courses offered by other departments in the business school upon approval
Note: List of electives may vary per academic year
Non-Credit 1: External speakers are invited throughout the year to enhance the experiential learning component of the MS in Finance program. Students are required to attend such meetings, and participation is assessed on a pass/fail basis.
Non-Credit 2: Students are required to pass the online ethics module from the Chartered Financial Analyst (CFA) Institute by the end of the first semester. Successful completion is a prerequisite of the Fundamentals of Finance II course.