The Villanova MSF curriculum balances foundational courses with the opportunity to explore your interests through a wide variety of related electives. The curriculum is designed to enable you to gain the exposure and skills most relevant to your intended career path within finance.
- Corporate Finance (Online and self-paced)
- Accounting primer (self-passed – pass/fail)
- Introduction to Quantitative Methods in Finance (Python)
Course description for Intro to Quantitative Methods in Finance using Python: "Covers the necessary programming, probability, statistical, and data management skills necessary for quantitative finance. Students will learn the fundamentals of Python while being exposed to the powerful libraries that makes Python such a popular language in this field."
- Investment Banking
A survey course in corporate finance with applications to investment banking. It develops an understanding of fundamental concepts and theories in finance and applies them to a wide range of practical business problems including those related to the financial services industry.
- Fixed Income
This course provides an introduction to fixed income markets and securities. Topics include techniques of valuation, interest rate determination and modeling, interest rate risk management, and bond portfolio management and strategies.
- Portfolio Management
A hands-on class where students manage real-dollar portfolios using various investment approaches. All students participate in live portfolio management while developing their financial analysis skills through a combination of rigorous fundamental research and quantitative techniques. Students have the chance to learn from market practitioners and industry experts.
- Derivatives and Risk Management
A comprehensive introduction to the markets for options, forwards, futures, swaps and other related derivative instruments. The course is designed to develop an understanding of how derivatives markets operate, how derivatives are priced and how they are used.
- Professional Development .5 credits
- Introduction to Quantitative methods in finance using Rs
- Elective credits
Students complete 12 elective credits. At least six credits must be taken from Group I (MSF electives), with the option to take up to 12 credits in Group I. Students can take up to 6 credits from Group II (non-MSF electives). Please see below for a sample of elective offerings. Please note that this sample list is neither comprehensive nor final, as non-MSF electives are subject to scheduling and availability through other graduate programs.
- Professional Development
- Financial Markets and Institutions
An advanced course that surveys the key topics and inter-relationships between financial markets, financial institutions and market microstructure design. Students apply the theories learned in this course to numerous problems facing today’s financial institutions and markets.
- Alternative Investments
This course exposes students to the growing market for investments in non-traditional asset classes such as private equity, venture capital, hedge funds, commodities, natural resources, and real estate. The course will examine the risk-return characteristics of alternative investments, their correlation with conventional asset classes, and their use within diversified portfolios.
- Portfolio Management II
A continuation of Portfolio Theory and Applications I, a hands-on class where students manage real-dollar portfolios using various investment approaches. All students participate in live portfolio management while developing their financial analysis skills through a combination of rigorous fundamental research and quantitative techniques. Students have the chance to learn from market practitioners and industry experts.
- Quantitative Finance
The course provides a framework for understanding quantitative asset management by first overviewing pertinent quantitative equity research then by replicating and backtesting existing research insights to provide hands-on experience for financial model building, valuation and quantitative performance attribution. The class aims to develop student skills that are best suited for quantitative asset management, valuation and advisory, data analytics, risk management, and statistical arbitrage roles, while providing students with insights into the asset management industry landscape that are particularly relevant to quantitative equity researchers.
- MBA 8139 Topic: Programming Business Model
This course is an introduction to programming that focuses on the design of computer applications, modern software engineering principles, object-oriented design and systems thinking. The course emphasizes good programming style with strong testing skills and the use of application programming interfaces to interact with real-time financial data. The course is explicitly designed for business students seeking to enhance analytical talents by developing stronger problem-solving skills, learning how to more easily manipulate data and gaining an appreciation for the integration of business systems. The Python programming language will be used.
- MBA 8529 Business Risk Management
This course examines contemporary risk management frameworks, overviews common regulatory reporting requirements and provides practical insights on effective business risk management to help students navigate today's dynamic marketplace.
- MBA 8800 Commercial Real Estate Investment
An overview of commercial real estate investment. The course empasizes the life cycle from acquisition through disposition using analytical and practical tools. Topics include market analysis, valuation, deal structuring, commercial leases, financing, investment management, marketing and careers in real estate.
- MBA 8350 Analyzing and Leveraging Data
The course begins with a review of descriptive statistics, confidence intervals and hypothesis testing. These tools will be extended into regression analysis geared towards analyzing large data sets in order to make informed business decisions.
- MBA 8529 Programming in R
The statistical programming language R is rapidly becoming the language of choice for business analysts due to its full array of software capabilities for data preparation, analysis, and graphical display. This course covers the fundamentals of the usage of R as a programming language, with emphasis on applications in business. Students will learn how to use the software environment of R to efficiently source, manipulate and analyze data.
- MBA 8531 International Business Management
Provides an overview of economic and cultural integration, trade problems, and tariff barriers, and highlights the conflicts and compromises between the executive polices and national objectives of various countries. The course emphasizes the development of marketing strategies and the problems concerning overseas investment and financing.
- MBA 8444 – Multinational Financial Management
Course covers globalization and the multinational corporation, foreign direct investment and political risk, international parity conditions, the foreign exchange market, the currency derivatives market, foreign exchange risk management, foreign trade financing, and managing the multinational financial system.
- MAT 7404 Statistical Methods
Topics include data summarization and display, distributionsc, binomial, Poisson, normal, t, chi-square and F, estimation, hypothesis testing, linear regression, correlation and statistical software packages.