- [Instructor] It's important to understand that the…character and the composition of the U.S. Stock Markets…has been changing over the last 20 years.…In fact, despite the fact fact that the U.S. Stock Market…continues to rise in value, the stock market has…been shrinking by another metric.…The number of publicly traded firms over time has shrunk.…The number of publicly traded firms peaked in…in the late 1990's at a little under 10,000.…Ever since then, there's been a slow, inexorable…decline in the number of public trade firms,…as illustrated in this graphic.…
Now, why is all this important?…Well the reality is that because there are fewer…companies out there, this leads to what we call…greater market efficiencies.…Market efficiency simply means that a…stock already incorporates all known information…into its price.…That would mean that there are no stocks that…are undervalued, and no stocks that are overvalued.…All of the prices out there are fair given what…we know at a particular point in time.…
That doesn't mean bad news can't happen…
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.