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Course Date: 12 September 2014 to 07 November 2014 (8 weeks)
Find out how modern electronic markets work, why stock prices change in the ways they do, and how computation can help our understanding of them. Build algorithms and visualizations to inform investing practice.
Tucker Balch is an associate professor in the School of Interactive Computing. He is also a co-founder of Lucena Research, LLC, a startup that delivers hedge fund software technologies to professional investors. His research at Georgia Tech focuses on machine learning for automated perception, and for understanding the behavior of social animals. Balch has published two books and over 150 technical articles in journals and conferences.
Overview Why do the prices of some companies’ stocks seem to move up and down together while others move separately? What does portfolio “diversification” really mean and how important is it? What should the price of a stock be? How can we discover and exploit the relationships between equity prices automatically? We’ll examine these questions, and others, from a computational point of view. You will learn many of the principles and algorithms hedge funds and investment professionals use to maximize return and reduce risk in equity portfolios.
We start with a tour of the mathematics and statistics that underlie equity price changes, and the relationships between different groups of equities. We’ll review the most important economic theories of investing and how to create programs that take advantage of them. We’ll look at the data needed to do this, and how to manipulate it effectively. Take a look at the course syllabus here.
Important note: This is a project oriented course involving Python programming.
Be sure this course is right for you! This course is intended for folks who have a strong programming background, but who are new to finance and investing. Check out the two links below to see if the course is a good match.
Signature track: This is a brand new option offered by Coursera. More information below.
Outcomes for regular and signature tracks At the end of the course you will have created a working market simulator that you can use to test your own investing strategies. You will understand the basic principles of Modern Portfolio Theory and Active Portfolio Management.
Workload On average you can expect to spend up to 8 to 12 hours per week on programming.
Will I get a certificate after completing this class? If you complete the project track, you will receive a Statement of Accomplishment. If you do not complete the projects you will not receive a Statement of Accomplishment. You can also optionally enroll in the Signature Track. What is Signature Track? Signature Track is a new option that will give students in select classes the opportunity to earn a Verified Certificate for completing their Coursera course. Signature Track securely links your coursework to your identity, allowing you to confidently show the world what you’ve achieved on Course. Joining a course’s Signature Track is optional. You can still fully participate in the course if you decide not to join, and you will still receive the standard Statement of Accomplishment if you successfully complete the free course, though this Statement will not be able to attest to your real identity. Learn more.
What resources will I need for this class? You will need a PC or Mac with an internet connection. To complete the projects you will need to install Python and several other Python libraries on your machine. We would be providing detailed instructions on the installation process. What is the coolest thing I'll learn if I take this class? You will build a working stock market simulator that you can use to test investing strategies.
The course will be 8 weeks long with two modules covered each week. Each module will be presented as several 8 to 15 minute segments. The modules will be followed by a multiple choice quiz. Assignments using Excel and the Python programming language will be provided.