Introduction

Hedge funds are among the most influential forces in today’s financial markets. These private pools of capital invest client assets across a wide range of asset classes and employ differentiated techniques to generate returns beyond what is offered by traditional long-only investing.

This course provides an introduction to the more commonly-known hedge fund strategies (equity-oriented, macro-focused, and arbitrage). The material examines the intuition behind these strategies and offers practical guidance for building/prototyping them Excel and in financial engineering toolsets such as R. Students will learn the entire lifecycle of strategy development, from conceptualization to implementation.

Course Objectives

This course seeks to introduce students to different hedge fund strategies and the application of financial engineering techniques in the pursuit of non-traditional returns. Students will also learn about the technical requirements of developing a quantitative investment strategy. 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:

1. Understand the theoretical and practical features of different hedge fund strategies
2. Understand the structural organization of hedge funds and their emphasis on alpha generation, risk and, portfolio management
3. Leverage financial engineering techniques to achieve non-traditional returns
4. 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.

Graduate Student Code of Academic Integrity

All Stevens graduate students promise to be fully truthful and avoid dishonesty, fraud, misrepresentation, and deceit of any type in relation to their academic work. A student’s submission of work for academic credit indicates that the work is the student's own. All outside assistance must be acknowledged. Any student who violates this code or who knowingly assists another student in violating this code shall be subject to discipline. All graduate students are bound to the Graduate Student Code of Academic Integrity by enrollment in graduate coursework at Stevens. It is the responsibility of each graduate student to understand and adhere to the Graduate Student Code of Academic Integrity. More information including types of violations, the process for handling perceived violations, and types of sanctions can be found here.

Inclusivity Statement

Stevens Institute of Technology believes that diversity and inclusiveness are essential to excellence in education and innovation. Our community represents a rich variety of backgrounds, experiences, demographics, and perspectives and Stevens is committed to fostering a learning environment where every individual is respected and engaged. To facilitate a dynamic and inclusive educational experience, we ask all members of the community to:

• 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

Prerequisites

A background in econometrics, probability and statistics, with a basic level of programming, is required. Proficiency in Excel is extremely helpful in this class. Learn the keyboard shortcuts!

Textbook

Key References
• [1]Lasse H. Pedersen, Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined, Princeton University Press (2015).

Optional References
• [2] Jack D. Schwager, Hedge Fund Market Wizards, Wiley Finance Series (2012).

Grading Procedures

Attendance (5%): Attendance is taken each lecture. Regular attendance and active participation will be a portion of the course grade assessment.

Classroom Exercise (25%): In-class work reinforces the course content and provides students with the opportunity to apply what they have learned in group settings.

Midterm Exam (30%): There will be one examination covering the core material of the course. The exam is open-book (online) and must be completed independently.

Course Project (40%): This course features a multi-week project that requires students to design and implement an investment strategy based on course material and discussion. Teams should be no more than 4 students per group. The course project is assessed on the thoroughness of the strategy (50%) and delivery of the presentation (50%).