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.
- Define what a share of stock is.
- Classify the type of trading that attempts to capitalize on the bid-ask spread.
- Name the rule that can be used as a metric for Fed interference in the market.
- State the first step in a data analysis project.
- Identify the type of characteristic algorithmic trading relies on.
- Break down how VAR is used to manage risk.
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.