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The 2016 US presidential election, opinion polls and the stock market

Author

Listed:
  • Kamal Upadhyaya
  • Raja Nag
  • Demissew Ejara

Abstract

Purpose - The purpose of this paper is to study the impact of the 2016 presidential election polls on the stock market. Design/methodology/approach - The empirical model includes daily stock returns as the dependent variable and past asset prices, 10-year treasury rates, opinion polls and VIX (market uncertainty) as explanatory variables with a one-year lag. The model was estimated using two sets of daily polling data: from July 1, 2015, to November 8, 2016, and from June 1, 2016, to November 8, 2016. Additional descriptive statistics, such as means and standard deviations, were also calculated. Findings - The estimated results did not reveal any statistically significant effects of opinion polls in favor of one candidate over another on stock returns. Simple statistical tests, however, show that the market performed better when Trump held a polling advantage over Clinton. Originality/value - To the best of the authors’ knowledge, this is the only study that has examined the effects of the 2016 presidential election polls on the US stock market. This study adds value to the understanding of the relationship between election polls and the stock market in the USA.

Suggested Citation

  • Kamal Upadhyaya & Raja Nag & Demissew Ejara, 2023. "The 2016 US presidential election, opinion polls and the stock market," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 16(2), pages 194-204, December.
  • Handle: RePEc:eme:jfeppp:jfep-10-2023-0310
    DOI: 10.1108/JFEP-10-2023-0310
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    More about this item

    Keywords

    Clinton; Trump; Presidential election; Opinion poll; Stock market; E44; G10;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    Statistics

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