Using Causal Inference to quantify layoff impact on stock price

Originally as this blog post in my personal blog:

Goal

SAP is a huge world-leading software company, and even world-leading companies apparently go through rough patches and reestructuring, as it has happened with SAP over the past few years. Part of this process included a major layoff of 6.000 people in January 2024. The market responded quite positively, with their stock price on the NY Stock Exchange going up a few percent over the following weeks (and it hasn't gone down since). Was the layoff causally related with the uptick in stock price? Or was it just a coincidence? We're gonna use Causal Inference estimation methods to identify and measure the impact of this particular layoff on their stock price, if there was any at all.

Result

Thanks to Google's CausalImpact R package and some correlated stock as predictors, we calculate a posterior probability of causal effect of 99,89%. 😎

Data
Code

Tools

R and a few of its packages:

• CausalImpact
• MarketMatching
• tidyquant