FE571 Quantitative Hedge Fund Strategies
Course Catalog Description
Hedge funds are among the most influential participants in the financial markets. These private investment pools have many unique features and vary significantly from one another. Common hedge fund strategies include those that are equity-oriented, macro-focused, and arbitrage strategies. This course provides an introduction to different hedge fund strategies, their economic intuition, and practical guidance for implementing quantitative strategies using
financial engineering toolsets such as the R programming language. Topics such as the lifecycle of developing a sound trading strategy, from conceptualization to implementation and validation/back-testing will be introduced.
Anshul K. Sharma
|By Appointment (Email)
|Tuesday 6:30 – 9:00 PM
This course aims to introduce students to different hedge fund strategies and the application of financial engineering techniques in the pursuit of non-traditional returns. It also helps students
to understand the technical requirements of developing a quantitative trading program. This course is designed for graduate students in the Financial Engineering program at the School of Systems and Enterprises.
By the end of the course, students will be able to:
- Understand the theoretical and practical features of different hedge fund strategies
- Understand the structural organization of hedge funds and their emphasis on alpha generation, risk and, portfolio management
- Leverage financial engineering techniques to achieve non-traditional returns
- Develop a quantitative trading program, seeing the project from idea generation to testing to implementation and participating in the investment competition at the end of the course.
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- Be open to the perspectives of others
- Appreciate the uniqueness of their colleagues
- Take advantage of the opportunity to learn from each other
- Exchange experiences, values, and beliefs
- Communicate in a respectful manner
- Be aware of individuals who are marginalized and involve them
- Keep confidential discussions private
A background in econometrics, probability and statistics, with a basic level of R programming, is required. FE515 (Introduction to R) is recommended.
Lasse H. Pedersen, Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined, Princeton University Press (2015).
-  Jack D. Schwager, Hedge Fund Market Wizards, Wiley Finance Series (2012).
Class Participation (20%): Attendance will be taken. Attendance is taken each week. Regular attendance and
active participation will be a portion of the course grade assessment.
Midterm Exam (40%): There will be one examination covering the core materials of the course. The exam is open-book and must be completed independently. Students are not allowed to work or discuss with other students.
Course Project (40%): This course features a multi-week project that requires students to design and implement a trading strategy based on course materials and discussion. Team should be no more than 4 students per group. The course project is further assessed based on the performance of the strategy (50%) and delivery of the presentation (50%).
|L1: Course Introduction / HF Introduction
|L2: Performance & Alpha
|L3: Alpha & Backtesting
|L4: Portfolio Risk & Trading
|L5: Fundamental Equity Strategies
|L6: Quantitative Equity Strategies
|L7: tatistical Arbitrage Strategies
|NO CLASS: SPRING BREAK
|L8: Macro Strategies
|L9: Managed Futures Strategies
|L10: Event Driven Strategies & Course Project
|L11: Fixed Income Arbitrage Strategies & Midterm
|L12: Fixed Income Arbitrage Strategies (cont’d)
|L13: Convertible Arbitrage Strategies
|L14: COURSE PROJECT PRESENTATION