- [Instructor] Now that we understand a little bit about…basic trading strategies for the VIX,…we might want to go a little bit deeper…and explore if there's any kind of relationships…between the VIX or perhaps the broader stock market…and some of the macroeconomic variables that we could gather…through publicly available sources like FRED.…To do that I want to go through and calculate…the correlation between the VIX…and four different variables of interest.…In particular, I'm going to look at the BBB bond yields,…the BBB bond yields lag by one day,…GDP, the change in GDP, and the Treasury rates.…
Now to do this, to explore these relationships…at least on a basic level,…I'm simply going to start by computing the correlations…between the VIX and a couple of the other variables…that I'm interested in.…And we'll start with the BBB bond indicator.…What we observe here is that the correlation…between the VIX and the BBB bonds…appears to be relatively low.…We'll talk more about that in just a moment, though.…
So let's go through and calculate our other correlations.…
Released
3/14/2018Professor 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.
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Video: Economic data and stock correlations