Curriculum
The master's degree in finance from the W. P. Carey School of Business at Arizona State University delivers a leading-edge finance curriculum with two academic tracks to help you align your degree with your career goals. Courses in the 32 credit hour, 9-month corporate finance and investments curriculum culminate in a capstone project, enabling you to build on concepts as you move through the program.
Optional 3rd Semester Track
In addition to the 9-month core curriculum, the MSFIN program offers an optional 3rd semester track, allowing you to strengthen your skills and knowledge in one specific area of big data. The analytics methods track will consist of four courses, as well as a summer internship opportunity and one additional credit of career preparation, taking you through goal setting and action planning for your next step.
At the start of the program, students will declare a degree track. You can choose to do the two semester track, or you can declare a 3rd semester of study and pursue a 16-month track in Analytics Methods.
Note: Registration for all degree courses is completed by the Program Operations team. Curriculum is subject to change.
Course Schedule
| Course | Credit Hours |
|---|---|
| Quarter 1 | |
| FIN 509: Quantitative Methods in Finance I | 3 |
| ACC 502: Financial Accounting | 3 |
| FIN 502: Managerial Finance | 3 |
| Quarter 2 | |
| FIN 535: Quantitative Methods in Finance II | 3 |
| FIN 525: Investment Strategies | 2.5 |
| FIN 530: Derivatives | 2.5 |
| Quarter 3 | |
| FIN 550: Fixed Income Securities | 2.5 |
| FIN 560: International Finance and Investments | 2.5 |
| FIN 545: Advanced Corporate Finance | 2.5 |
| Quarter 4 | |
| FIN 565: Risk Management in Bank and Financial Institutions | 2.5 |
| FIN 555: Entrepreneurial Finance or FIN 597: Artificial Intelligence and Machine Learning Applications in Finance |
2.5 |
| FIN 575: Finance Capstone | 2.5 |
Course Descriptions
FIN 509: Quantitative Methods in Finance I
Empirical investigation of properties of financial data, such as basic probability theory, matrix algebra, ordinary least squares, and maximum likelihood estimation. Explores methods through both algebraic derivation and programmed implementation in Python. Provides the basis for portfolio optimization by focusing on the estimation and testing of financial factor models.
ACC 502: Financial Accounting
Contemporary financial accounting and reporting systems; emphasizes the interpretation and evaluation of a company's external financial reports.
FIN 502: Managerial Finance
Introduction to contemporary finance theory and the application of analytical techniques to make optimal decisions under uncertainty. Course topics include statistical properties of asset returns; portfolio optimization techniques using linear algebra and differential calculus; tests of asset pricing using linear regression; sensitivity of capital budgeting outcomes using Monte Carlo simulations; mathematics of bond pricing and option valuation techniques using binomial trees; and the Black-Scholes option pricing model.
FIN 535: Quantitative Methods in Finance II
Empirical investigation of financial data, using techniques such as autoregressive and vector-autoregressive models, dimension-reduction techniques motivated by latent factor models, and machine learning dimension-reducing techniques. Methods are explored using algebraic derivation and implementation in Python. Builds upon statistical and programming skills developed in FIN 509 and emphasizes forecasting for the optimization of portfolios.
FIN 525: Investment Strategies
Presents the fundamental principles of risk and return, portfolio diversification, asset allocation, efficient markets, active portfolio management, portfolio evaluation. Reviews selected alternative investment strategies such as hedge fund investments.
FIN 530: Derivatives
Intermediate- to advanced-level course in derivative assets such as options, forward and futures contracts, swaps and financial engineering.
FIN 550: Fixed Income
Intermediate- to advanced-level course in fixed income instruments and associated relative valuation of the securities.
FIN 560: International Finance
Examines the financial issues of an international investment decision. Main topics include foreign exchange market, investment alternatives in the international capital markets, and the management of foreign exchange risk.
FIN 545: Advanced Corporate Finance
Studies major decision-making areas and selected topics in corporate finance. Attempts to develop decision-making ability in these areas using both lectures & cases.
FIN 565: Risk Management in Banks and Financial Institutions
The objective of this course is to provide students with a risk management view of financial institutions (or financial intermediaries). Traditionally, banking courses have focused on an overview of the financial services industry, sector by sector, concentrating on balance sheet presentations and overlooking management decision making and risk management. In contrast, this course will emphasize a risk management approach.
FIN 555: Entrepreneurial Finance
The objective of this course is to provide an overview of the economics and institutions involved in entrepreneurial finance. Our focus will be on the financing of new ventures. The class will consist primarily of case analysis, supplemented with in-class exercises and lecture material.
FIN 597: Artificial Intelligence and Machine Learning Applications in Finance
Exploration of modern artificial intelligence and machine learning technologies, applications, techniques, and implications for financial decision-making. Knowledge of linear algebra, basic probability theory and calculus along with programming skills in Python are required for this course.
FIN 575: Finance Capstone
The objective of this course is to provide students with a culminating experience as a step in completing the degree. The course applies finance principles related to the investment, risk management, and financing policies of the firm to develop decision-making ability in these areas. Analysis of finance problems through selected readings and case studies will be emphasized.
Optional 3rd Semester Specialization Track - Immersion
In addition to the 9-month core curriculum, the MSFIN program offers an optional 3rd semester track, allowing you to strengthen your skills and knowledge in one specific area of big data. The analytics methods track is 12 credit hours, with a minimum of two required courses and two required electives, as well as a summer internship opportunity and one additional credit of career preparation, taking you through goal setting and action planning for your next step.
Some potential courses include:
- Some potential courses include:
- Python for Data Analysis
- Career Coaching
- Introduction to Enterprise Analytics
- Data Mining I
- Blockchain
- Business Data Visualization
Contact your Program Manager, Calli Townsend at [email protected] for details!