The Impact of Major Political Announcements on Abnormal Returns in Large-Cap Technology Stocks Compared with the S&P 500

Abstract

This study examines the impact of five major political announcements on the cumulative abnormal returns of three large cap technology stocks (Apple, Microsoft and Nvidia) relative to the broad S&P 500 benchmark over the period of January 2022 to April 2025. This study used the standard event methodology based on MacKinlay, daily abnormal returns were calculated using the market model with an estimation period of 120 to 11 trading days prior to each event. The 5 events examined were the 2024 US presidential election, the Liberation Day tariff announcement, semiconductor export controls on China, the EU Digital Markets Act compliance deadline, and the signing of the CHIPS and Science Act. Out of 15 individual stock-event observations, only one produced statistically significant results, Apple during the EU Digital Markets Act compliance deadline. The technology basket only outperformed the raw S&P 500 market in only one out of the five events, this failed to support the initial hypothesis that large cap technology stocks generate higher abnormal returns relative to the broad S&P 500 market. Limitations include the small number of stocks identified, the small number of events analysed which restricts the generalisability of the conclusions.

Introduction

The S&P 500 is a stock market index of 500 of the largest publicly traded companies in the United States. It acts as a benchmark for the overall performance of the U.S. stock market. As larger companies have a higher influence on the index, the index’s movements are disproportionately driven by its largest holdings, and today, large-cap companies such as Apple, Microsoft and Nvidia make up a large proportion of the index’s value. This raises the possibility that political announcements in favour of large-cap technology companies can cause sharp abnormal movement of the entire index.

Major political announcements such as elections, international relations, and tariffs have historically had a strong impact on technology companies. This is because tech companies rely heavily on international markets. This warrants further investigation of whether large-cap technology companies react more strongly to political announcements than the overall market. While researchers have already studied the impact of political announcements on the market generally, few studies focus on comparing large-cap companies to the broad S&P 500 after influential political announcements such as elections and tariffs. This paper aims to reach a clear conclusion on whether large-cap technology companies show abnormal movements that are different in size from the broad S&P 500 around major political announcements. The hypothesis of this study is that large-cap tech companies have statistically significant CARs exceeding the S&P 500 benchmark return over the same event window following political events.

To reach a conclusion, daily stock price data for a group of large cap technology companies (Apple, Nvidia and Microsoft) and the S&P 500 are collected from Yahoo Finance. Using the estimation period, a market model, each stock’s actual returns are compared to the expected return, and these are summed into a cumulative abnormal return (CAR) for each event. The CARs of the technology basket are then compared to the S&P 500’s return over the same event period to discover whether technology stocks reacted more greatly to political announcements than the S&P 500, which acted as the broad market in this study.

Literature Review

The event study methodology used in this study was first formalized by Fama, Fisher, Jensen and Roll, who made the framework of using financial market to examine the impact of specific events on stock returns by separating abnormal returns from expected market returns. Their foundational study demonstrated that stock prices adjust rapidly and efficiently to new information, establishing the theoretical basis for measuring abnormal returns around specific events. MacKinlay (1997) later provided the most widely cited and comprehensive framework for conducting event studies in economics and finance, establishing the market model as the standard approach for estimating expected returns and formalising the calculation of cumulative abnormal returns over a defined event window. This study directly follows the methodology outlined by MacKinlay (1997), using an estimation window of 120 to 11 trading days prior to each event and a symmetric event window of (−5, +5) trading days.

The relationship between political announcements and reaction of stock market has been studied in depth in existing literature. Boutchkova, Doshi, Durnev and Molchanov P (2012) established that industries that are exposed to government policies tend to exhibit significantly high stock return volatility around major political announcements. Their findings demonstrate that political uncertainty is not uniformly spread across all sectors with technology companies facing disproportionate exposure due to their reliance on international trade, regulatory frameworks, and government contracts. This relates with the current study of which examines whether large-cap technology stocks generate abnormal returns that differ meaningfully from the broad market around major political announcements.

The buy the rumour sell the news phenomenon is well documented in the behavioural finance literature. Brunnermeier showed that informed traders preempt anticipated positive announcements, building positions in advance and liquidating them once the event occurs, causing prices to decline despite the positive nature of the announcement. The comprehensive legislative discussion surrounding the CHIPS and Science Act for months before its official signing in August 2022 allowed markets to anticipate its expected advantages, clarifying the unexpected negative cumulative abnormal return seen for Nvidia during the event window.

While the existing literature has extensively studied the impact of political announcements on stock markets generally, only a few studies focus specifically on comparing the abnormal returns of individual large cap technology stocks against the broad S&P 500 market across a range of different political events. Most existing studies either examine the technology sector as a whole, focus on a single type of political event or compare across industries rather than comparing individual stocks. This study contributes to the existing literature by providing firm level evidence across five distinct categories of political announcement, demonstrating that the specificity and direct financial impact of a political announcement on an individual firm is a stronger determinant of abnormal return magnitude than the scale or visibility of the announcement itself.

Methodology

This study uses the daily closing prices of three large cap technology companies (Apple, Microsoft and Nvidia) and the S&P 500 index from January 3, 2022 to April 30, 2025 collected from Yahoo Finance. The five major political announcements selected for this study were the 2024 US presidential elections, the liberation day tariff announcement, semiconductor export controls on China, the EU Digital Markets Act compliance deadline, and the signing of the CHIPS and Science Act. These were selected to provide a variety of types of announcements relevant to the technology sector.

Table 1Event Dates Used as Day Zero

Event	Date Used as Day Zero
CHIPS Act Signed	August 9, 2022
Chip Export Controls	October 7, 2022
EU DMA Compliance	March 6, 2024
2024 Election	November 6, 2024
Liberation Day Tariffs	April 2, 2025

Daily returns for each stock were calculated using:

R_{t} = \frac{P_{t} - P_{t - 1}}{P_{t - 1}}

Where $P_{t}$ is the closing price on day t and $P_{t - 1}$ is the closing price on the previous trading day.

The sensitivity of returns of a stock relative to the index (β) was calculated using:

β_{i} = \frac{Cov (R_{i}, R_{m})}{Var (R_{m})}

$Cov (R_{i}, R_{m})$ is the covariance between the return of stock i and the market return, $Var (R_{m})$ is the variance of the market return, $(R_{i})$ is the return of stock i, and $(R_{m})$ is the return of the market.

The average return of the stock that is not explained by market movement ( $α_{i})$ was calculated by:

α_{i} = {\bar{R}}_{i} - β_{i} \cdot {\bar{R}}_{m}

Where ${\bar{R}}_{i}$ is the mean return of stock i during the estimation window, $β_{i}$ is the beta of stock i, and ${\bar{R}}_{m}$ is the mean market return during the estimation window.

The expected daily return for each stock prior to the political announcement was calculated using the market model from 120 to 11 days prior to the announcement:

R_{i, t} = α_{i} + β_{i} \cdot R_{m, t} + ϵ_{i, t}

$α_{i}$ is the alpha of stock i representing return independent of market movements, $β_{i}$ is the beta of stock i, $R_{m, t}$ is the market return on day t, and $ϵ_{i, t}$ is the error term representing the portion of return unexplained by the market model.

The abnormal daily return for each stock was calculated using:

{AR}_{i, t} = R_{i, t} - (α_{i} + β_{i} \cdot R_{m, t})

$R_{i, t}$ is the actual return of stock i on day t, $α_{i}$ is the alpha of stock i, $β_{i}$ is the beta of stock i, and $R_{m, t}$ is the market return on day t.

Daily abnormal returns within the event window were summed to obtain the cumulative abnormal return (CAR) for each stock and event by using:

{CAR}_{i} (t_{1}, t_{2}) = \sum_{t = t_{1}}^{t_{2}} {AR}_{i, t}

where $AR$ is the abnormal return of a specific stock on a specific day, $t_{1}, t_{2}$ is start and end days of the event window.

To determine whether each CAR was statistically significant, this formula was used:

t = \frac{{CAR}_{i}}{σ ({AR}_{i}) \times \sqrt{n}}

Where $σ ({AR}_{i})$ is the standard deviation of abnormal returns during the estimation window, and n is the number of trading days in the event window.

Results

Overview

This study analysed the cumulative abnormal returns of the selected three stocks across the five major political announcements. 15 observations were produced yet only 1 of them produced a statistically significant result at the p < 0.05 level: Apple during the EU Digital Markets Act compliance deadline. All remaining 14 observations failed to reach statistical significance, suggesting that for most events, the observed abnormal returns could not be distinguished from random market noise.

Table 2Cumulative Abnormal Returns by Event and Stock

Event	Stock	CAR (%)	t-statistic	p-value	Significant (p<0.05)
2024 Election	AAPL	−7.59	−1.815	0.0695	No
2024 Election	MSFT	−3.21	−1.197	0.2313	No
2024 Election	NVDA	−5.95	−0.645	0.5192	No
2024 Election	Tech Basket	−5.58	–	–	–
2024 Election	S&P 500 (raw return)	+2.64	–	–	–
Liberation Day Tariffs	AAPL	−5.55	−1.289	0.1975	No
Liberation Day Tariffs	MSFT	+5.34	1.448	0.1476	No
Liberation Day Tariffs	NVDA	+9.57	1.114	0.2653	No
Liberation Day Tariffs	Tech Basket	+3.12	–	–	–
Liberation Day Tariffs	S&P 500 (raw return)	−4.92	–	–	–
Chip Export Controls	AAPL	−2.17	−0.666	0.5052	No
Chip Export Controls	MSFT	−2.27	−0.682	0.4954	No
Chip Export Controls	NVDA	−3.32	−0.455	0.6494	No
Chip Export Controls	Tech Basket	−2.59	–	–	–
Chip Export Controls	S&P 500 (raw return)	−1.39	–	–	–
EU DMA Compliance	AAPL	−7.36	−2.613	0.0090	Yes
EU DMA Compliance	MSFT	−0.73	−0.223	0.8238	No
EU DMA Compliance	NVDA	+9.42	1.664	0.0961	No
EU DMA Compliance	Tech Basket	+0.44	–	–	–
EU DMA Compliance	S&P 500 (raw return)	+1.73	–	–	–
CHIPS Act Signed	AAPL	+1.04	0.325	0.7453	No
CHIPS Act Signed	MSFT	−0.20	−0.058	0.9540	No
CHIPS Act Signed	NVDA	−6.65	−0.887	0.3751	No
CHIPS Act Signed	Tech Basket	−1.94	–	–	–
CHIPS Act Signed	S&P 500 (raw return)	+4.48	–	–	–

Breakdown of Each Event

2024 Election

During the 2024 Election, all of the stocks from the technology basket produced a negative cumulative abnormal return. Apple declined the most at −7.59%, followed by Nvidia at −5.95% and Microsoft at −3.21%. The technology basket overall produced an average CAR of −5.58% significantly different from the S&P 500 which produced a 2.64% gain over the event window. None of the stocks from the technology basket reached a statistical significance. While the broad market reacted positively to the elections, large cap technology stocks can be seen underperforming relative to the expected returns.

Liberation Day Tariffs

The Liberation Day tariffs produced the most contrasting results across the basket. While Apple produced a CAR of −5.55%, Microsoft produced +5.34% and Nvidia produced +9.57%. The technology basket averaged a positive CAR of +3.12%, outperforming the S&P 500 which fell −4.92% over the same window. Despite the large magnitude of individual stock movements, none reached statistical significance. The divergence between Apple and the other two stocks may reflect Apple’s greater exposure to tariff-affected supply chains in China compared to Microsoft and Nvidia.

Chip Export Controls

The announcement of semiconductor export controls on China generated negative abnormal returns across all three technology stocks, Apple declined 2.17% while Microsoft and Nvidia suffered a 2.27% and 3.32% decline respectively. The technology basket underperformed the S&P 500, generating an average CAR of −2.59% compared to the market’s −1.39%. None of the results were statistically significant. Notably, Nvidia, whose products were most directly targeted by the export controls, produced the largest negative CAR among the three stocks.

EU DMA Compliance

The EU DMA Compliance produced the only statistically significant result in the whole study. Apple generated CAR of −7.36% (t = −2.613, p = 0.009), this indicated that the abnormal returns produced by Apple compared to the S&P 500 were statistically distinguishable from random variation. Microsoft and Nvidia showed contrasting movements of −0.73% and +9.42% respectively, though neither was significant. Yet, the technology basket produced a CAR of +0.44% underperforming the S&P 500’s +1.73% change.

CHIPS Act Signed

The signing of the CHIPS and Science Act, produced counterintuitive results. Nvidia produced a −6.65% change while Apple and Microsoft produced a +1.04% and −0.20% change respectively. The technology basket averaged −1.94% against the S&P 500’s strong gain of +4.48%. None of the results were statistically significant.

Discussion

Assessment of Hypothesis

The hypothesis of this study was that large-cap technology stocks would produce statistically significant abnormal returns compared to the S&P 500 following major political announcements, but the results proved otherwise. Only 1 out of the individual stock event observations following events depicted a statistically significant abnormal return and the tech basket only outperformed the S&P 500 in one of the 5 events examined.

EU DMA–Apple

The only statistically significant cumulative abnormal return in this study was produced by Apple during the EU Digital Market Act compliance. This event directly affected Apple as it targeted the App store practices obliging it to open its ecosystem to third party developers and alternative payment systems. As both Microsoft and Nvidia did not show any significant change during the same event, this further supports the interpretation.

CHIPS Act–Nvidia

The signing of the CHIPS and Science Act produced a counterintuitive result, while the legislation was expected to boost semiconductor production, Nvidia declined by 6.65%. This is consistent with the buy the rumour sell the news phenomenon, where investors anticipate a positive catalyst and accumulate positions and liquidate the stock after the event materializes. The CHIPS Act had been subject to extensive legislative discussion and media coverage for several months prior to its signing, providing adequate opportunity for markets to price in its expected change.

Limitations

This study had multiple limitations which should be acknowledged. First, the technology basket only consisted of 3 stocks which limits the generalisability of the findings to the broad large cap technology sector. Other companies like Google, Amazon and Meta were not part of the basket but their reaction could be different to the same event.

Second, only 5 events were taken into consideration for this study, inadequate enough to produce a strong general conclusion about the relationship between large cap technology stocks and political announcements.

Third, the event window used (−5, +5) while being used consistently in standard event study methodology, may or may not capture the stock’s full reaction to the event. Some events cause prolonged reaction beyond the 11-day window.

Fourth, two of the five events occur within close proximity in the data, raising the possibility that their estimation windows overlap, which could contaminate the expected return calculations and introduce bias into the abnormal return estimates.

Finally, the technology basket’s cumulative abnormal returns are compared against the S&P 500’s raw return over the event window. As these both measure different concepts, abnormal returns adjusted for expected movements versus actual index returns, this comparison should be interpreted as descriptive rather than a direct measure of outperformance, and may overstate or understate the true divergence between technology stocks and the broader market.

Conclusion

This study examined the impact of five major political announcements on the CARs on large cap technology stocks. The selected stocks were Apple, Microsoft and Nvidia. They were compared to the broad S&P 500 market benchmark over the period January 2022 to April 2025. This study used standard event study methodology, daily abnormal returns were calculated using the market model and summed into cumulative abnormal returns over a symmetric (−5, +5) event window for each stock and event combination.

The results from the study do not support the hypothesis that large cap technology stocks generate statistically significant cumulative abnormal returns exceeding the S&P 500 following major political announcements. Out of 15 individual stock-event observations, only one reached statistical significance — Apple’s CAR of −7.36% during the EU Digital Markets Act compliance deadline (t = −2.613, p = 0.009). The technology basket only outperformed the S&P 500 in one out of the five events examined. However the findings reveal that company-specific regulatory actions targeting a single firm’s core business model are considerably more likely to produce statistically detectable abnormal returns than broad macroeconomic or legislative announcements.

Future research should address the limitations of this study by expanding the stock sample to include a broader range of large-cap technology companies, including a larger number of political events across different regulatory environments, and applying portfolio level significance testing to the technology basket as a whole. Extending the event window beyond (−5, +5) trading days may also capture more prolonged market reactions to certain types of political announcements. Such expansions would allow for more robust and generalisable conclusions about the relationship between political announcements and abnormal returns in the technology sector.

References

Boutchkova, M., Doshi, H., Durnev, A. and Molchanov P. (2012) ‘Precarious politics and return volatility’, Review of Financial Studies, 25(4), pp. 1111–1154.

Brunnermeier, M.K. (2005) ‘Information leakage and market efficiency’, Review of Financial Studies, 18(2), pp. 417–457.

Duso, T., Gugler, K. and Yurtoglu, B. (2010) ‘Is the event study methodology useful for merger analysis?’, International Review of Law and Economics, 30(2), pp. 186–192.

Fama, E.F. (1970) ‘Efficient capital markets: a review of theory and empirical work’, Journal of Finance, 25(2), pp. 383–417.

Fama, E.F., Fisher, L., Jensen, M.C. and Roll, R. (1969) ‘The adjustment of stock prices to new information’, International Economic Review, 10(1), pp. 1–21.

MacKinlay, A.C. (1997) ‘Event studies in economics and finance’, Journal of Economic Literature, 35(1), pp. 13–39.

AI Disclosure

Artificial intelligence tools including Claude and ChatGPT were used solely for grammar correction, language improvement and assistance in writing the data collection code during the preparation of this paper.