Professor Michael McDonald provides a brief primer on securities markets. He explains how data helps investors forecast performance and automate trading. Then he moves into the practical steps: coming up with algorithmic trading rules and developing and testing an algorithm. Finally, he shows how the algorithm can be applied and eventually expanded to other securities. Anyone working in financial services, or interested in investing in the stock market, will be able to use these tutorials to understand and develop simple trading algorithms of their own.
- Basics of trading stocks
- Algorithms and the financial industry
- How the Fed regulates algorithmic trading
- Case studies
- Quantitative rules and strategies
- Gathering data for algorithms
- Designing algorithms
- Testing algorithms
- Buying and selling with trading algorithms
Skill Level Intermediate
- [Michael] Hi, I'm Dr. Michael McDonald. I'm a professor of finance and a data science researcher. I've taught quantitative finance and financial forecasting in the financial markets to executives and traders of financial firms, hedge funds, securities regulators, and many large companies. In this course I'm going to show you how to use data to do basic algorithmic trading. In particular, I'll help you to understand how to evaluate trade strategies, test them, and determine if they're feasible as the cornerstone in an investment vehicle.
We're going to learn all about how big companies take data and use it to make money in the financial markets. I hope you'll join me.