Quantitative Finance Major
With major challenges like fintech implementation and integration, globalization, new regulations and other industry innovations, financial services employers are saying they need skilled people with computer science, engineering, mathematics, statistics and econometrics training now more than ever. New positions in the financial industry now require not just knowledge of finance but also quantitative and technical skills.
Curriculum in the Quantitative Finance major integrates economics, mathematics, and computer science with financial theory and application. It is designed to help you develop the mathematically demanding quantitative skills and fintech expertise required in today’s rapidly changing financial services industry
Our innovative new core curriculum includes increased quantitative rigor and emphasis on technology. Our students will graduate prepared to launch a finance career having mastered quantitative techniques and able to solve complex business problems.
Thanks to the new STEM designation, which is based on strict curriculum guidelines defined by the U.S. Department of Homeland Security, international students who graduate with a Quantitative Finance major can apply for a 24-month OPT STEM Extension to their 12-month
Optional Practical Training (OPT) period, allowing them to work in the U.S. for up to 36 months after graduation.
You may complete the curriculum in 12 months. This program has been designed to be compliant with F1 visa regulations. Classes begin in September.
Download the MS in Quantitative Finance curriculum map to view the typical program timeline.
Required Quantitative Finance 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 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 3333 | 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 a set of modern analytical tools to solve practical problems in finance with the goal of building operational models, testing them with data, and then using them to aid financial decision making. Topics include regression, event studies, the empirical behavior of security prices, market efficiency, and performance evaluation.
FINA 6334 | 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
Elective Quantitative Finance Courses (Select 4)
Faculty are hard at work to develop this course. Description will be added soon.
FINA 6338|3 credits
Offers an intensive study of econometric techniques applied to cross-section, time-series, and panel data. Applies the fundamentals of econometrics to analyzing structural economic models, forecasting, and policy analysis. Computer applications and an empirical research project are an integral part of the course.
ECON 5140 | 4 credits
Studies various computational methods in finance. Analyzes market data and build trading strategies. Uses interpolation, solver, and optimization methods to calibrate discount curve and volatility surfaces to market prices. Analyzes market data and applies dimension-reduction techniques such as principal component analysis (PCA). Applies time-series analysis and PCA to implement and back test trading strategies.
FINA 6337 | 3 credits
Introduces relational database management systems as a class of software systems. Prepares students to be sophisticated users of database management systems. Covers design theory, query language, and performance/tuning issues. Topics include relational algebra, SQL, stored procedures, user-defined functions, cursors, embedded SQL programs, client-server interfaces, entity-relationship diagrams, normalization, B-trees, concurrency, transactions, database security, constraints, object-relational DBMSs, and specialized engines such as spatial, text, XML conversion, and time series. Includes exercises using a commercial relational or object-relational database management system.
CS 5200 | 4 credits
Covers qualitative and quantitative aspects of entrepreneurial finance, such as venture capital and angel financing. Also covers private equity (i.e., buyout/leveraged buyout firms) but in less detail. Introduces students to valuation aspects in entrepreneurial finance, including valuation of startups, using real options to value innovation-intensive firms; valuation in staged financing; etc. Case-work emphasizes the practical aspects of qualitative and quantitative issues related to venture capital financing, entrepreneurship, and innovation from the perspective of the financier and the startup firm. Also covers many issues related to the venture capital industry, such as the limited partnership structure of the venture capital/private equity industry, venture capital term sheets and contracts, exit of portfolio firms, and international investments. May be repeated without limit.
FINA 6260 | 3 credits
Introduces financial modeling applications in the fields of risk management, statistics applied to finance, investments, and portfolio management. Financial modeling is used for performing financial analysis facilitating business decision making in virtually any business. Excel is the most widely used electronic spreadsheet program in the world. Offers students an opportunity to develop strong Excel proficiency needed to effectively and efficiently understand and implement the quantitative aspects of financial topics covered in the various financial courses taught in the MBA and MSF programs and to learn how to use a variety of spreadsheet tools and techniques to enhance their overall analytical skill set.
FINA 6207 | 3 credits
Exposes students to theory, applications, and evidence concerning highly sensitive interest-rate products. Designed for students seeking to develop understanding of fixed-income valuation and hedging methods and familiarity with major markets and instruments. Emphasizes tools for quantifying, edging, and speculations. Topics include duration; convexity; approaches to modeling the yield curve; interest-rate forward; futures, swaps, and options; credit risk and credit derivative; mortgages; and securitization.
FINA 6336 | 3 credits
Introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Topics include heuristic search and game trees, knowledge representation using predicate calculus, automated deduction and its applications, problem solving and planning, and introduction to machine learning. Required course work includes the creation of working programs that solve problems, reason logically, and/or improve their own performance using techniques presented in the course. Requires experience in Java programming.
CS 5100 | 4 credits
Develops specific concepts, policies, and techniques for the financial management of the multinational firm. Topics include operation of the foreign exchange markets, foreign exchange risk management, sources and instruments of international financing, foreign direct investment and the management of political risk, multinational capital budgeting, and financing control systems for the multinational firm.
FINA 6204 | 3 credits
Explores the environments that have recently given rise to a large number of corporate mergers and the business factors underlying these corporate combinations. Examines the financial, managerial, accounting, and legal factors affecting mergers. Studies how to appraise a potential merger and structure a merger on advantageous terms.
FINA 6214 | 3 credits
Provides students with a comprehensive understanding of real estate finance. Emphasizes factors affecting real estate investment. Topics include valuation (appraisal), market analysis, development, taxation, ownership types, short-term financing, mortgage markets, and investment strategies. Designed for students interested in a general overview of real estate finance, as well as those intending to pursue a career in the real-estate field.
FINA 6217 | 3 credits
Develops portfolio construction, revision, and performance measurement. Highlights portfolio construction in an efficient capital market. Topics include risk-return analysis, the effects of diversification on risk reduction, and the costs of inflation, taxes, and transaction costs on fixed income and equity security portfolios. Examines financial models of capital asset pricing as the basis for the analysis of portfolios from the institutional investor’s viewpoint.
FINA 6219 | 3 credits
Explores recent developments in financial management and financial analysis through the use of modern finance theory to make capital allocation decisions that lead to long-run value maximization for the corporation. Focuses on applications and financial model building, risk analysis for valuation applications, and business strategies to measure and manage corporate value and value creation. Topics are relevant to value consultants, corporate managers, and securities analysts.
FINA 6216 | 3 credits
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