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Do opinion polls move stock prices? Evidence from the US presidential election in 2016

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  • Herold, Michael
  • Kanz, Andreas
  • Muck, Matthias

Abstract

This paper analyzes stock returns before and during the 2016 US presidential election. This election stands out because both nominees Clinton and Trump were frequently characterized to have very different profiles and the outcome was considered as a major surprise. We explore the relationship between polling data and stock prices during the pre-election period. To measure the impact of polling data on stock prices, we develop the “Trump Head-to-Head Momentum” (THHM) reflecting increasing poll scores for Trump during election uncertainty. Implementing a GARCH-in-Mean model, we find that the measure is significantly related to industries representing about 30% of the market capitalization. Moreover, we find that THHM-based active trading strategies outperform passive strategies after the election. This also suggests that stock prices have been exposed to changes in the probability of the event “Trump wins the election” in the pre-election period.

Suggested Citation

  • Herold, Michael & Kanz, Andreas & Muck, Matthias, 2021. "Do opinion polls move stock prices? Evidence from the US presidential election in 2016," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 665-690.
    • Handle: RePEc:eee:quaeco:v:80:y:2021:i:c:p:665-690
    DOI: 10.1016/j.qref.2021.03.013
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    as
    1. Turan G. Bali & Nusret Cakici & Xuemin (Sterling) Yan & Zhe Zhang, 2005. "Does Idiosyncratic Risk Really Matter?," Journal of Finance, American Finance Association, vol. 60(2), pages 905-929, April.
    2. Jinliang Li & Jeffery A. Born, 2006. "Presidential Election Uncertainty And Common Stock Returns In The United States," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 29(4), pages 609-622, December.
    3. Michael C. Herron & James Lavin & Donald Cram & Jay Silver, 1999. "Measurement of Political Effects in the United States Economy: A Study of the 1992 Presidential Election," Economics and Politics, Wiley Blackwell, vol. 11(1), pages 51-81, March.
    4. Andrea Mattozzi, 2008. "Can we insure against political uncertainty? Evidence from the U.S. stock market," Public Choice, Springer, vol. 137(1), pages 43-55, October.
    5. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    6. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    7. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2007. "Partisan Impacts on the Economy: Evidence from Prediction Markets and Close Elections," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(2), pages 807-829.
    8. Gemmill, Gordon, 1992. "Political risk and market efficiency: Tests based in British stock and options markets in the 1987 election," Journal of Banking & Finance, Elsevier, vol. 16(1), pages 211-231, February.
    9. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    10. Bialkowski, Jedrzej & Gottschalk, Katrin & Wisniewski, Tomasz Piotr, 2008. "Stock market volatility around national elections," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1941-1953, September.
    11. Tim Bollerslev & Julia Litvinova & George Tauchen, 2006. "Leverage and Volatility Feedback Effects in High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 353-384.
    12. Elijah Brewer & James M. Carson & Elyas Elyasiani & Iqbal Mansur & William L. Scott, 2007. "Interest Rate Risk and Equity Values of Life Insurance Companies: A GARCH–M Model," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 74(2), pages 401-423, June.
    13. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    14. Hanke, Michael & Stöckl, Sebastian & Weissensteiner, Alex, 2020. "Political event portfolios," Journal of Banking & Finance, Elsevier, vol. 118(C).
    15. Raymond Fisman & Eric Zitzewitz, 2019. "An Event Long-Short Index: Theory and Applications," American Economic Review: Insights, American Economic Association, vol. 1(3), pages 357-372, December.
    16. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    17. Child, Travers Barclay & Massoud, Nadia & Schabus, Mario & Zhou, Yifan, 2021. "Surprise election for Trump connections," Journal of Financial Economics, Elsevier, vol. 140(2), pages 676-697.
    18. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    19. repec:bla:jfinan:v:58:y:2003:i:3:p:975-1008 is not listed on IDEAS
    20. Roland Füss & Michael Bechtel, 2008. "Partisan politics and stock market performance: The effect of expected government partisanship on stock returns in the 2002 German federal election," Public Choice, Springer, vol. 135(3), pages 131-150, June.
    21. Demissew Diro Ejara & Raja Nag & Kamal P. Upadhyaya, 2012. "Opinion polls and the stock market: evidence from the 2008 US presidential election," Applied Financial Economics, Taylor & Francis Journals, vol. 22(6), pages 437-443, March.
    22. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    23. Goodell, John W. & Vähämaa, Sami, 2013. "US presidential elections and implied volatility: The role of political uncertainty," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1108-1117.
    24. Amit Goyal & Pedro Santa‐Clara, 2003. "Idiosyncratic Risk Matters!," Journal of Finance, American Finance Association, vol. 58(3), pages 975-1007, June.
    25. Ang, Andrew & Gorovyy, Sergiy & van Inwegen, Gregory B., 2011. "Hedge fund leverage," Journal of Financial Economics, Elsevier, vol. 102(1), pages 102-126, October.
    26. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    27. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    28. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    29. Robert F. Stambaugh & Jianfeng Yu & Yu Yuan, 2015. "Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle," Journal of Finance, American Finance Association, vol. 70(5), pages 1903-1948, October.
    30. Wagner, Alexander F. & Zeckhauser, Richard J. & Ziegler, Alexandre, 2018. "Company stock price reactions to the 2016 election shock: Trump, taxes, and trade," Journal of Financial Economics, Elsevier, vol. 130(2), pages 428-451.
    31. Elyasiani, Elyas & Mansur, Iqbal, 1998. "Sensitivity of the bank stock returns distribution to changes in the level and volatility of interest rate: A GARCH-M model," Journal of Banking & Finance, Elsevier, vol. 22(5), pages 535-563, May.
    32. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    33. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    34. Bali, Turan G., 2008. "The intertemporal relation between expected returns and risk," Journal of Financial Economics, Elsevier, vol. 87(1), pages 101-131, January.
    35. Fu, Fangjian, 2009. "Idiosyncratic risk and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 91(1), pages 24-37, January.
    36. Jobson, J D & Korkie, Bob M, 1981. "Performance Hypothesis Testing with the Sharpe and Treynor Measures," Journal of Finance, American Finance Association, vol. 36(4), pages 889-908, September.
    37. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    38. Maria Boutchkova & Hitesh Doshi & Art Durnev & Alexander Molchanov, 2012. "Precarious Politics and Return Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 25(4), pages 1111-1154.
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    More about this item

    Keywords

    Presidential election uncertainty; Pre-election information; Opinion polls; Industry returns; GARCH-M; Market efficiency;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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