A new study suggests that the amount of attention paid to Donald Trump online helps predict optimism on Wall Street. Published in American Behavioral Scientist, the research indicates that spikes in Google searches for the former president tend to precede increases in bullish sentiment among individual investors. This relationship appears to have grown stronger in the period following the 2024 U.S. election.
The financial world has traditionally operated under the assumption that markets are rational. This view holds that asset prices reflect all available information regarding economic fundamentals, such as corporate earnings, interest rates, and employment data. However, the field of behavioral finance challenges this perspective. It argues that human psychology, cognitive biases, and collective emotion play a significant role in how investors make decisions.
Political figures have always influenced markets, but typically this occurs through specific policy decisions or legislative actions. Donald Trump represents a shift in this dynamic. His influence is often exerted through a pervasive media presence and direct communication styles rather than traditional policymaking channels alone. The researchers wanted to understand if the sheer volume of attention a political figure generates can act as a signal for market mood, independent of specific policy details.
“We were motivated by a clear gap between two well-established literatures that rarely talk to each other: behavioral finance has shown that investor sentiment moves markets, and political communication research has shown that media attention shapes public perceptions, but few studies connect political attention directly to financial sentiment,” said study author Raúl Gómez Martínez, an associate professor at Rey Juan Carlos University in Madrid.
“Donald Trump offered a unique real-world case because his media presence is unusually intense and persistent, even outside formal policymaking, raising the question of whether attention alone can influence market psychology. We therefore wanted to test whether high-frequency digital signals, such as Google search activity, could capture this transmission mechanism and help explain weekly changes in retail investor optimism. In short, the study addresses the broader problem of how political narratives spill over into financial markets beyond traditional fundamentals.”
The study builds on the concept that attention is a finite resource. In the digital age, what captures the public’s focus often drives their economic expectations. The researcher sought to test whether the visibility of Donald Trump, a figure closely associated with pro-business narratives, directly impacts investor sentiment. This phenomenon is often referred to by market analysts as the “Trump trade,” where his political prominence signals potential deregulation and tax cuts.
To investigate this connection, the research team analyzed weekly data spanning from April 5, 2020, to October 12, 2025. This timeframe provided a total of 289 weekly observations. The researchers utilized Google Trends to measure public attention. This tool indexes search interest on a scale from zero to 100 rather than providing raw search numbers. It allows for a standardized comparison of interest over time.
The researchers tracked the search term “Donald Trump” within the United States to gauge the intensity of public focus. For investor sentiment, they relied on data from the American Association of Individual Investors (AAII). This non-profit organization conducts a weekly survey asking its members if they feel bullish, bearish, or neutral about the stock market over the next six months. The study focused specifically on the percentage of respondents who reported a bullish or optimistic outlook.
The research team employed statistical models known as ordinary least squares regressions. This method helps identify relationships between the search data and the sentiment survey results. They aimed to see if variations in one variable could explain variations in the other. Additionally, the researchers employed Granger causality tests. This statistical technique helps determine if one time series is useful in forecasting another, effectively checking if changes in attention happen before changes in sentiment.
The analysis revealed a positive association between search volume and investor optimism across the entire five-year period. When online searches for Trump increased, self-reported bullish sentiment among individual investors tended to rise in the same week. The Granger causality analysis provided evidence that the search activity occurred before the shift in sentiment. This suggests that public attention flows into market optimism rather than market optimism driving the search traffic.
The researchers then isolated the data from the period following the 2024 election. This subsample covered the weeks from November 3, 2024, to October 12, 2025. In this smaller set of 50 weeks, the connection between attention and sentiment became much more pronounced. The statistical model explained approximately 15 percent of the variation in investor sentiment during this post-election phase. This is a notable increase compared to about 2 percent for the full five-year period.
The strength of the relationship more than doubled in the post-election data. This indicates that in times of heightened political activity or uncertainty, the market becomes more sensitive to political visibility. The authors suggest that the political context acts as an amplifier. When Trump is at the center of the news cycle during a critical political transition, his visibility becomes a stronger driver of economic expectations for retail investors.
“What we show is that media attention becomes a directly observable, quantifiable variable with real explanatory power for market dynamics,” Gómez Martínez told PsyPost. “Even though the full-sample fit is modest (R²≈0,02), this is common in finance, where sentiment is influenced by many overlapping factors; what matters is that attention consistently adds incremental information.”
“In more sensitive political contexts, the explanatory power rises markedly (R²≈0,15 and a coefficient more than double), indicating that this signal becomes substantially more relevant when uncertainty or polarization is high. In that sense, political attention measured through Google Trends can function as a new complementary market indicator—an additional behavioral barometer that investors and analysts can use alongside traditional economic and financial variables to inform investment decisions.”
These findings imply that financial markets are not driven solely by economic spreadsheets. Collective attention and mass psychology serve as measurable drivers of financial expectations. For the average person, this suggests that everyday news consumption and online behavior can indirectly influence prices by shifting the general mood of investors.
“Our findings show that spikes in public interest in a highly visible political figure like Donald Trump, measured through Google searches, tend to precede increases in investor optimism, meaning that media attention itself can shape market mood,” Gómez Martínez explained. “This suggests that everyday news consumption and online behavior can indirectly influence prices by affecting sentiment, especially among retail investors. In short, politics and digital attention are not just background noise—they can become measurable drivers of financial expectations and market dynamics.”
The study provides a practical application for the theories of behavioral finance. It moves beyond the anecdotal observation that politics moves markets to providing statistical evidence. It supports the idea that high-profile figures can serve as exogenous drivers of sentiment. Their media dominance can shape market psychology even before any concrete policies are enacted.
“Nothing in the results truly surprised us, because they were broadly consistent with what behavioral finance and attention-based theories would predict: highly visible political figures should influence expectations and, therefore, investor sentiment,” Gómez Martínez said. “What was important for us was not discovering an unexpected effect, but demonstrating it rigorously with data, using an econometric framework and supervised regression techniques that allow us to quantify and test the relationship formally.”
“In other words, we moved from an intuitive or anecdotal idea—’politics moves markets’—to statistically validated evidence. That empirical validation is what gives the findings credibility and practical value for both researchers and practitioners.”
While the findings provide evidence of a link between political attention and market mood, the study has certain limitations. The sentiment data comes from the American Association of Individual Investors, which reflects the views of retail investors rather than large institutional firms. Retail investors are often considered more susceptible to behavioral biases and media influence than professional fund managers. It is possible that institutional investors interpret these attention spikes differently.
Google Trends measures the volume of searches but not the intent behind them. A spike in searches could result from negative controversies just as easily as positive news. The tool does not distinguish between a supporter searching for rally dates and a critic searching for details on a scandal. The current study assumes the attention is generally interpreted through the lens of the “Trump trade,” but it does not qualitatively analyze the content of the news driving the searches.
The researchers also note that financial markets are complex ecosystems influenced by countless variables simultaneously. Political attention is one factor among many.
“A potential misinterpretation we would like to preempt is the idea that media attention to a single political figure ‘drives the market’ by itself,” Gómez Martínez told PsyPost. “Our results do not imply that political searches replace fundamentals such as earnings, interest rates, or macroeconomic news; rather, they show that attention adds an additional behavioral layer that helps explain changes in sentiment at the margin. Financial markets are influenced by many overlapping forces, so this variable should be understood as complementary, not deterministic.”
Future research could incorporate sentiment analysis of news headlines. This would allow researchers to determine the tone of the media coverage alongside the volume. Expanding the scope to include institutional investor data would help determine if professional traders react similarly to retail investors. The researchers also suggest applying this methodology to other political figures to see if the phenomenon is unique to Trump.
“This paper is part of an ongoing collaboration between researchers at Universidad Rey Juan Carlos (URJC) and Dublin City University (DCU), and it represents just one step in a broader research agenda focused on understanding investor sentiment as a measurable and actionable variable,” Gómez Martínez explained. “Our long-term goal is to continue developing models that integrate behavioral indicators—such as digital attention, surveys, and online activity—alongside traditional financial data to improve how markets are analyzed and forecasted.”
“We currently have several related articles in progress that expand this line of work using alternative sentiment proxies and more advanced econometric and supervised machine-learning regression techniques to strengthen predictive performance. Importantly, this research also has practical transfer through my fintech, InvestMood, where these insights are applied to build algorithmic trading systems that help investors incorporate sentiment-based signals into real-world investments.”
“Perhaps the most important point to add is that this study illustrates how the growing availability of digital behavioral data is changing the way we can analyze financial markets,” Gómez Martínez said. “Tools such as Google Trends allow us to observe collective attention almost in real time, something that was simply not possible a decade ago, and this opens new opportunities to measure psychological and social drivers of market movements more precisely.”
“More broadly, we hope the paper encourages researchers and practitioners to think beyond purely fundamental variables and to treat attention and sentiment as legitimate, quantifiable components of market dynamics. In that sense, the study is not only about one political figure, but about demonstrating a methodology that can be applied to many other contexts where public narratives influence financial expectations.”
The study, “The Strengthening Link Between Donald Trump’s Online Attention and Wall Street Sentiment,” was authored by Raúl Gómez Martínez, Camilo Prado Román, María Luisa Medrano García, Aref Mahdavi Ardekani, and Damien Dupré.
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