Tesla Stock Plunge: How Controversy and Market Trends Impact Investors
In this blog, I explore the impact of Elon Musk’s controversial gesture on Tesla’s stock performance. I analyze it using the statistical method Causal Impact, which estimates the effect of the event by comparing it to a counterfactual scenario. The results highlight how significant this effect was in the context of the broader tech stock sell-off.
Tesla stocks analysis
In recent weeks (this blog is written in mid-March 2025), we have been experiencing a sell-off in tech stocks (though not exclusively). While this is driven by a complex mix of factors, many are tied to events happening in the U.S. In particular, Trump’s policies have increased uncertainty for businesses, consumers, and investors.
n this blog, we will focus on one specific event and its impact on Tesla’s stock performance compared to selected tech and car manufacturing companies. We explore the effect of Musk’s controversial gesture. The analysis leverages the tidyquant package to retrieve stock prices from Yahoo Finance and the CausalImpact package to estimate the event’s effect based on counterfactual outcomes. The goal is to assess what portion of Tesla’s stock decline can potentially be attributed to reactions following the event. We acknowledge that stock prices are influenced by numerous factors, and this analysis is a simplification. Additionally, after this event, Musk made several more controversial statements and actions that may have also influenced Tesla’s stock price.
Disclaimer: I am not an economist, and this is a quick analysis using the mentioned methods.
Data overview
The chart below displays the stock prices of selected companies. The line color represents the type of company—tech (blue), car manufacturing (green), and Tesla (red). The vertical dashed line marks the event date. It is evident that Tesla’s stock price is more volatile than that of other companies, with a more pronounced decline.
The tech stocks used for comparison as control variables include: Apple (AAPL), Microsoft (MSFT), NVIDIA (NVDA), Amazon (AMZN), Meta (META), Alphabet (GOOG), Broadcom (AVGO), and Oracle (ORCL).
The car manufacturing stocks used as control variables include: General Motors (GM), Ford (F), Toyota (TM), Stellantis (STLA), Honda (HMC), and Ferrari (RACE).
Causal Impact analysis
Causal Impact is a statistical method used to estimate the causal effect of an event (or intervention) on a time series. It is based on a Bayesian structural time-series model, which estimates the counterfactual (i.e., what would have happened without the event) and compares it to observed data. The counterfactual is derived using a set of control variables selected based on the data. The difference between the observed and counterfactual data represents the estimated effect of the event. This model assumes the effect of the intervention remains constant over time.
The following chart illustrates the estimated impact of the event on Tesla’s stock price. The the solid black line represents the observed data, dashed blue line represents the counterfactual (what would have happened without the event), and the shaded area represents the 95% confidence interval. Since the two lines are very close to each other during the pre-event period, we can assume that the model is well specified.
The model estimates that the event had a negative impact on Tesla’s stock price. The estimated effect is approximately -16% with a 95% confidence interval of [-23%, -8%]. The probability of obtaining this effect by chance is very low (Bayesian one-sided tail-area probability p = 0.001), meaning the causal effect is statistically significant. On the last available date, the estimated effect is -127 USD compared to what we would expect.
Posterior inference {CausalImpact}
Average Cumulative
Actual 335 12724
Prediction (s.d.) 408 (19) 15507 (730)
95% CI [365, 441] [13857, 16774]
Absolute effect (s.d.) -73 (19) -2783 (730)
95% CI [-107, -30] [-4050, -1133]
Relative effect (s.d.) -18% (4%) -18% (4%)
95% CI [-24%, -8.2%] [-24%, -8.2%]
Posterior tail-area probability p: 0.00118
Posterior prob. of a causal effect: 99.88249%
For more details, type: summary(impact, "report")Summary
The analysis suggests that the event on January 20, 2025, and the subsequent reactions had a significant negative impact on Tesla’s stock price. However, this analysis is based on a simplified model, and stock prices are influenced by many factors. The model assumes that the effect of the event remains constant over time, which may not hold true in reality. Further improvements could be made by incorporating additional control variables or using a more customized model.
It is also reasonable to assume that Musk’s subsequent controversial actions and statements contributed to further fluctuations in Tesla’s stock price.
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