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Fundamental uncertainty and stock market volatility

Author

Listed:
  • Ivo Arnold
  • Evert Vrugt

Abstract

We provide empirical evidence on the link between stock market volatility and macroeconomic uncertainty. We show that US stock market volatility is significantly related to the dispersion in economic forecasts from participants in the Survey of Professional Forecasters over the period 1969 to 1996. This link is much stronger than that between stock market volatility and the more traditional time-series measures of macroeconomic volatility, but disappears from 1997 onwards. This coincides with a previously documented regime shift in stock volatility. Macroeconomic uncertainty is also able to explain and forecast the volatilities of the Fama and French factors SMB, HML and UMD.

Suggested Citation

  • Ivo Arnold & Evert Vrugt, 2008. "Fundamental uncertainty and stock market volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 18(17), pages 1425-1440.
    • Handle: RePEc:taf:apfiec:v:18:y:2008:i:17:p:1425-1440
    DOI: 10.1080/09603100701857922
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    References listed on IDEAS

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    1. Victor Zarnowitz & Phillip Braun, 1993. "Twenty-two Years of the NBER-ASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 11-94, National Bureau of Economic Research, Inc.
    2. Ciaran Driver & Lorenzo Trapani, 2004. "Cross Section Vs Time Series Measures of Uncertainty: Using UK Survey Data," Econometric Society 2004 North American Summer Meetings 330, Econometric Society.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," NBER Technical Working Papers 0279, National Bureau of Economic Research, Inc.
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    6. Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia, 2022. "Economic uncertainty and structural reforms: Evidence from stock market volatility," Quantitative Economics, Econometric Society, vol. 13(2), pages 467-504, May.
    7. Liu, Wei & Garrett, Ian, 2023. "Regime-dependent effects of macroeconomic uncertainty on realized volatility in the U.S. stock market," Economic Modelling, Elsevier, vol. 128(C).
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    14. Brockhaus, Jan & Kalkuhl, Matthias, 2014. "Can the Agricultural Market Information System (AMIS) help to reduce food price volatility?," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170391, Agricultural and Applied Economics Association.
    15. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    16. Jin Guo, 2015. "Causal relationship between stock returns and real economic growth in the pre- and post-crisis period: evidence from China," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 12-31, January.
    17. Guerello, Chiara, 2016. "The effect of investors’ confidence on monetary policy transmission mechanism," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 248-266.
    18. Albaity, Mohamed Shikh, 2011. "Impact of the monetary policy instruments on Islamic stock market index return," Economics Discussion Papers 2011-26, Kiel Institute for the World Economy (IfW Kiel).
    19. Huabin Bian & Renhai Hua & Qingfu Liu & Ping Zhang, 2022. "Petroleum market volatility tracker in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2022-2040, November.

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