- [Man] So we previously looked at developing a…rule, what we called the big buy rule,…which is based on the concept of only buying…the VIX, or its derivative linked securities…when the VIX is at least one standard deviation…below its 100 day moving average.…We want to continue that rule and evaluate it today.…We want to test and see whether this rule makes sense.…So if we come down to May 25th, 1990, 100 days…after our data points start, we've already got…our populations pre-filled.…
And I've added a few more rows to this.…So all we need to do now…is drag and drop our returns all the way to the bottom.…And what this will do is on the days when we choose to buy…with the big buy,…we will have a return equal to the big buy return.…So I'm going to add in the additional returns that we see…here, and so the first day, as an example,…we have a big buy because the investment,…in this case the VIX, is at least one standard…deviation below its moving average.…
The next day we don't invest,…the following day we do, et cetera.…
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.