These courses are not mandatory. MAFN students may choose their electives from across the university, subject to the constraints of the MAFN degree requirements and the constraints imposed by the schools and departments offering the courses.
Math GR 5220 Quantitative Methods in Investment Management
Surveys the field of quantitative investment strategies from a “buy side” perspective through the eyes of portfolio managers, analysts, and investors. Financial modeling there often involves avoiding complexity in favor of simplicity and practical compromise. All necessary material scattered in finance, computer science, and statistics is combined into a project-based curriculum, which gives students hands-on experience to solve real-world problems in portfolio management. Students will work with market and historical data to develop and test trading and risk management strategies. Programming projects are required to complete this course.
Math GR 5280 Capital Markets and Investments
Risk/return tradeoff, diversification and their role in the modern portfolio theory, their consequences for asset allocation, and portfolio optimization. Capital Asset Pricing Model, Modern Portfolio Theory, Factor Models, Equities Valuation, definition and treatment of futures, options, and fixed income securities will be covered. Many business school finance courses have a Capital Markets and Investments prerequisite, and Math GR5280 satisfies this prerequisite. However, even if you satisfy the prerequisite, there is no guarantee that you can cross-register into any particular business school course.
Math GR 5300 Hedge Funds Strategies and Risk
The hedge fund industry has continued to grow after the financial crisis, and hedge funds are increasingly important as an investable asset class for institutional investors as well as wealthy individuals. This course will cover hedge funds from the point of view of portfolio managers and investors. We will analyze a number of hedge fund trading strategies, including fixed income arbitrage, global macro, and various equities strategies, with a strong focus on quantitative strategies. We distinguish hedge fund managers from other asset managers and discuss issues such as fees and incentives, liquidity, performance evaluation, and risk management. We also discuss career development in the hedge fund context.
Math GR 5320 Financial Risk Management and Regulation
Prerequisites: The student is expected to be mathematically mature and to be familiar with probability and statistics, arbitrage pricing theory, and stochastic processes. The course will introduce the notions of financial risk management, review the structure of the markets and the contracts traded, introduce risk measures such as VaR, PFE, and EE, overview regulation of financial markets, and study a number of risk management failures. After successfully completing the course, the student will understand the basics of computing parametric VaR, historical VaR, Monte Carlo VaR, credit exposures, and CVA and the issues and computations associated with managing market risk and credit risk. The student will be familiar with the different categories of financial risk, current regulatory practices, and the events of financial crises, especially the most recent ones.
Math GR 5340 Fixed Income Portfolio Management
Prerequisites: Students should be comfortable with algebra, calculus, probability, statistics, and stochastic calculus. The course covers the fundamentals of fixed income portfolio management. Its goal is to help the students develop concepts and tools for the valuation and hedging of fixed income securities within a fixed set of parameters. There will be an emphasis on understanding how an investment professional manages a portfolio given a budget and a set of limits.
Math GR 5420 Modeling and Trading Derivatives
Prerequisites: Math GR5010 Required: Math GR5010 Intro to the Math of Finance (or equivalent),Recommended: Stat GR5264 Stochastic Processes – Applications I (or equivalent). The objective of this course is to introduce students, from a practitioner’s perspective with formal derivations, to the advanced modeling, pricing and risk management techniques of vanilla and exotic options that are traded on derivatives desks, which goes beyond the classical option pricing courses focusing solely on the theory. It also presents the opportunity to design, implement and backtest vol trading strategies. The course is divided in four parts: Advanced Volatility Modeling; Vanilla and Exotic Options: Structuring, Pricing and Hedging; FX/Rates Components: Discounting, Forward Projection, Quanto and Compo Options; Designing and Backtesting Vol Trading Strategies in Python.
Math GR 5430 Machine Learning for Finance
The application of Machine Learning (ML) algorithms in the Financial industry is now commonplace but still nascent in its potential. This course provides an overview of ML applications for finance use cases, including trading, investment management, and consumer banking. Students will learn how to work with financial data and how to apply ML algorithms using the data. In addition to providing an overview of the most commonly used ML models, we will detail the regression, KNN, NLP, and time-series deep learning ML models using desktop and cloud technologies. The course is taught in Python using Numpy, Pandas, scikit-learn, and other libraries. Basic programming knowledge in any language is required.
Math GR 5510 MAFN Fieldwork
Prerequisites: all 6 MAFN core courses, at least 6 credits of approved electives, and the instructors’ permission. This course provides an opportunity for MAFN students to engage in off-campus internships for academic credit that counts towards the degree. Graded by letter grade. Students need to secure an internship and get it approved by the instructor. This course provides an opportunity for MAFN students to engage in off-campus internships for academic credit that counts towards the degree.This course helps the students understand the job search process and develop the professional skills necessary for career advancement. The students will not only learn the best practices in all aspects of job-seeking but will also have a chance to practice their skills. Each class will be divided into two parts: a lecture and a workshop. In addition, the students will get support from Teaching Assistants who will be available to guide and prepare the students for technical interviews.
Math GR 5520 Career Development for Quantitative Finance
This course helps the students understand the job search process and develop the professional skills necessary for career advancement. The students will not only learn the best practices in all aspects of job-seeking but will also have a chance to practice their skills. Each class will be divided into two parts: a lecture and a workshop. In addition, the students will get support from Teaching Assistants who will be available to guide and prepare the students for technical interviews.
NOTE: Offered to first semester MAFN students only.