Blog Post

Putting Corrections in Perspective using Power BI


My enthusiasm for analyzing stock market data using Power BI – even after publishing two posts recently (this and this) – is at all-time high, unlike the stock market itself. In today’s edition let’s try to put corrections in perspective.

September tensions

In the first report shown below, we can see that September, historically, has the worst performance.

power bi september stock performance

This report has three items:

  • A: Column chart shows the monthly average returns from 1950 to Oct, 2015. June, August, and September has negative returns and September is by far the worst month
  • B: Displays the returns in September throughout the years. You can see big drops several times in this month
  • C: When you look at 5 years with corrections in the recent past, you’ll notice that there were considerable drops in all of those 5 years. September is highlighted using background color, a trick I picked up from Jason Thomas

Corrections are common!?

The second report below again has three items.

power bi stock corrections perspective

  • A: Aug 2015 saw a decrease of approx. 5%. This marks the 39th worse month in all of the trading months from 1950 to Sep 2015
  • B: 40% of all the trading months were in negative territory, and 60% were in positive territory
  • C: Shows how long S&P 500 stays in a certain range from it’s previous high. For example 39% of the time, the index is less than it’s previous high

Every action may not have equal and opposite reaction

The last report tells one very important thing: big drops are sudden and fewer, gains are slow and occur more times than drops.

power bi stock corrections volatility

Bottom Line

These charts backed by data suggests that corrections happen all the time. Every time S&P index reaches all-time high it’ll be pulled back and it slowly sets a new high. If you’re interested in creating these visuals yourself, take a look at Tracking S&P 500 Using Power BI. I covered details about getting and the data and creating the charts there, so I’m sparing from all the steps again.

Disclaimer – This blog post isn’t investment advice nor am I qualified to advice you, on anything I might add.