- [Instructor] There are a variety of different types…of trading strategies that are very common…for pursuing algorithmic trading.…One of these types of training strategies…is called mean reversion.…The simplest strategies in algorithmic trading…are really based on mean reversion.…This includes types like pairs trades…which we've talked about previously.…For example, we might look at peers…like Walgreens and CVS or Ford and GM…or perhaps pairs of stocks that are directly related.…Things like Viacom shares A and B.…This type of mean reversion trade is very common…and I really trust to capitalize on the relationship…between two different securities.…
A little bit more advanced type of algorithmic trading…that's become very popular over the last decade…is built around what we call the four-factor model.…The four-factor model was developed by two economists,…Eugene Fama and Ken French…of the University of Chicago and Dartmouth, respectively.…The four-factor model identifies characteristics…of stocks or firms that do well on average over time.…
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.