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When I wrote the original post, I wasn’t planning on writing a follow-up. Certainly not the week after. But what a difference a week can make in a dynamic system like the US stock market.
While re-running the computations testing the latest version of RStudio, I noticed something surprising – President Trump’s rally has advanced to 2nd place!
A mere week ago, that seemed unthinkable. Something abnormal must have happened. Two things happened. First, the current stock market advanced another 2%. Nothing to brag about just another positive vote of confidence in the economy’s direction.
The more impactful reason behind this sudden switch became clear when I took a look at the President H.W. Bush’s rally. Even from the above chart, it’s clear the rally lost significant amount of steam within a day, or two max. Is this a problem with data? A bit of forensics:
election.date = "1988-11-08"
require(quantmod)
dj = getSymbols("^DJI", from="1900-01-01", auto.assign=F)
id = findInterval(as.Date(election.date), index(dj))
tail(ROC(Cl(dj[id:(id+239)]), type="discrete", na.pad=F))
And the truth reveals itself:
| Date | Return |
|---|---|
| 1989-10-12 | -0.49% |
| 1989-10-13 | -6.91% |
| 1989-10-16 | 3.43% |
| 1989-10-17 | -0.70% |
| 1989-10-18 | 0.19% |
| 1989-10-19 | 1.50% |
Low and behold, no problem with the data, just a 7% drop on October 13th 1989. A quick search reveals that this was indeed Friday the 13th mini-crash! Friday, the 13th … mini-crash … What a coincidence!
I will keep it brief and wrap up this post here. There were a few improvements and changes I did to the R code used to perform these analysis – the Gist contains all of them.
It’s all optimism in the air, judging by the market behavior at least.
The post Markets Performance after Election: Day 239 appeared first on Quintuitive.
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