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<p>This study examines the statistical association between opinion polls and stock market behavior during the 2024 U.S. Presidential Elections, specifically analyzing the risk-return dynamics of the S&amp;P 500 and NASDAQ indices. Using an Autoregressive Distributed Lag (ARDL) framework, we analyze the relationship between polling data (from Real Clear Politics and Morning Consult) and stock market returns, controlling for volatility (VIX) and Treasury yields. The data covers the election cycle from July 1 to November 8, 2024. The results indicate that stock market movements are primarily associated with historical trends and volatility rather than daily polling fluctuations. The ARDL analysis reveals no statistically significant relationship between polling spreads and stock prices. Consequently, we reject the hypotheses that polls act as immediate market movers for the S&amp;P 500 (H1) and NASDAQ (H2). Unlike prior studies focused on singular election cycles, this research integrates multiple polling sources with an advanced econometric approach to provide comprehensive insights. Additionally, this study contributes to the growing literature on political uncertainty and market dynamics by uniquely focusing on the differentiated market responses across key election periods in 2024 using high-frequency data and sentiment-adjusted polling variables. External economic variables and geopolitical risks may also impact stock fluctuations, suggesting future studies should include broader macroeconomic factors. Investors should prioritize economic indicators and volatility indices over polling data for market predictions. Findings highlight the need for policy transparency to maintain investor confidence amid political uncertainty.</p>

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Polls, Politics, and Profits: The 2024 US Presidential Election’s Economic Ripples

  • 期刊论文

  • 发表日期：

    2026年1月29日

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  • Neha Kamboj,
  • Sanju Rani

摘要

This study examines the statistical association between opinion polls and stock market behavior during the 2024 U.S. Presidential Elections, specifically analyzing the risk-return dynamics of the S&P 500 and NASDAQ indices. Using an Autoregressive Distributed Lag (ARDL) framework, we analyze the relationship between polling data (from Real Clear Politics and Morning Consult) and stock market returns, controlling for volatility (VIX) and Treasury yields. The data covers the election cycle from July 1 to November 8, 2024. The results indicate that stock market movements are primarily associated with historical trends and volatility rather than daily polling fluctuations. The ARDL analysis reveals no statistically significant relationship between polling spreads and stock prices. Consequently, we reject the hypotheses that polls act as immediate market movers for the S&P 500 (H1) and NASDAQ (H2). Unlike prior studies focused on singular election cycles, this research integrates multiple polling sources with an advanced econometric approach to provide comprehensive insights. Additionally, this study contributes to the growing literature on political uncertainty and market dynamics by uniquely focusing on the differentiated market responses across key election periods in 2024 using high-frequency data and sentiment-adjusted polling variables. External economic variables and geopolitical risks may also impact stock fluctuations, suggesting future studies should include broader macroeconomic factors. Investors should prioritize economic indicators and volatility indices over polling data for market predictions. Findings highlight the need for policy transparency to maintain investor confidence amid political uncertainty.