- [Instructor] One of the most powerful tools…that we're going to be looking at using…in some of the algorithmic trading that we do later on…is what's called regression analysis.…Regression analysis is a business tool…that's used for predictions.…It's going to follow the basic formula…that you see on your screen here.…Y is equal to ax plus b,…where y is the variable that we're trying to predict,…x is some set of data that we've got,…and then a is what we call a coefficient.…It's the relationship between x and y,…and b…is some sort of base value,…otherwise called the y-intercept.…
Now, this type of simple formula is just the beginning.…Obviously, we're going to expand this over time,…and generally that's going to be done through a computer.…But it gives us the basis for the type of predictions…that our algorithms will be doing…when we're evaluating investment choices.…Now, our regression is going to predict…the dependent variable y…based on our set of independent variables x.…Essentially, what we're going here is a simple regression.…
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.