- The algorithms we've focused on throughout…this course have been focused around,…or built around a single security.…The reality is that diversification is key…to any portfolio, so when we're building…algorithmic trading strategies, we may start…by considering the trading in a single security,…but we should look for ways to compliment…trading in that particular security…with other algorithmic trading strategies.…For example, if we're going to be trading…the VIX, we may also want to be trading…another security that compliments it well.…
In particular, let's look for trading strategies…where we're using capital on say, Monday, Wednesday,…and Friday in trading strategy number one,…but not on Tuesday and Thursday,…and trading strategy number two uses…capital on Tuesday and Thursday.…Now, that's a simplistic example.…Obviously, particular trades are not going to be designated…based on the day of the week, in most cases,…but the point is that we want to look…for strategies that compliment one another.…Where either the two strategies together reduce…
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.