Technology and innovation are transforming the financial industry at a dramatic pace. Employers tell us they don’t just need leaders with financial expertise—they’re looking for advanced mathematical and technical skills as well.
That’s why we’ve designed our Full-Time MS in Finance/MBA – Quantitative curriculum to not only deepen your financial knowledge, but also to give you the background in financial technology and business analytics that will make you a valued asset to any company that hires you. You’ll study a challenging curriculum that integrates finance with other disciplines, such as economics, mathematics, and computer science. You’ll also hone your interpersonal skills and learn how to operate in the U.S. business environment through dedicated coaching and a career management class.
To earn an MS in Finance/MBA with a track in Quantitative Finance, you must complete the MS in Finance/MBA core curriculum (16 credits) and eighteen additional credits of Quantitative Finance Track coursework. Your remaining thirty-three credits will be your concentration and electives.
Quantitative Finance Track Required Courses
Introduces the basic framework of corporate finance and financial decision making. Topics include capital budgeting; capital investment decisions; complex valuations; security issues; dividend policy; static and dynamic capital structure; real option analysis; restructuring; bankruptcy; corporate control and governance; and the legal, ethical, and regulatory environment of financial management.
FINA 6331 | 3 credits
Introduces the essential fundamental mathematics needed for the study of modern finance: probability, stochastic processes, statistics, and regression analysis. Also focuses on theory and empirical evidence useful for investment decisions. Topics include financial risk factors, financial models, financial markets and equilibrium models of security prices, market efficiency, and the empirical behavior of security prices.
FINA 6332 | 3 credits
Familiarizes students with domestic and international financial markets and the securities traded therein. Discusses a variety of techniques for valuation of financial assets and relies heavily on quantitative methods. Critically analyzes such qualitative concepts as market efficiency, intrinsic value, and risk. The contents of this course, descriptive, theoretical, and applied, should provide students with the ability to build unique valuation models to suit the particular investment alternative they wish to scrutinize. Also provides students with an understanding of how investment theory and investment practice relate.
FINA 6203 | 3 credits
Introduces derivative assets, financial engineering, and risk management. Explores specific hedging use of options, forwards, and futures. Focuses on the determinants of forwards, futures, options and swaps, and various exotic derivatives pricing using computer-based numerical methods in a Monte Carlo setting and in closed form using elements of stochastic calculus. Also explores risk-management strategies using positions in derivative securities, static hedging, and dynamic hedging in continuous time.
FINA 6335 | 3 credits
Introduces Python and its use as a financial data analytics tool. Python has become one of the most widely used open-source, cross-platform programming languages. Covers the basics of programming in Python and key libraries (NumPy, Pandas, Matplotlib, etc.) used in data analytics, then focuses on implementing various financial models in Python. Topics include single and multifactor portfolio models, portfolio theory and the efficient frontier, algorithmic trading, options and futures, and value at risk.
FINA 6333 | 3 credits
Examines statistical methods used to analyze financial data and test financial theories. Offers students an opportunity to learn how to access various sources of financial data, design empirical tests, and apply basic programming skills to analyze the data and arrive at conclusions. Specific topics include regression analysis, time-series analysis, event study methodology, panel data analysis, and limited dependent variable models.
FINA 6334 | 3 credits
Complete 21 credit hours from the following:
The curriculum is subject to change by D’Amore-McKim faculty. Please monitor for updates.