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Stock market volatility and jumps in times of uncertainty

Author

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  • Megaritis, Anastasios
  • Vlastakis, Nikolaos
  • Triantafyllou, Athanasios

Abstract

In this paper we examine the predictive power of latent macroeconomic uncertainty on US stock market volatility and jump tail risk. We find that increasing macroeconomic uncertainty predicts a subsequent rise in volatility and price jumps in the US equity market. Our analysis shows that the latent macroeconomic uncertainty measure of Jurado et al. (2015) has the most significant and long-lasting impact on US stock market volatility and jumps in the equity market when compared to the respective impact of the VIX and other popular observable uncertainty proxies. Our study is the first to show that the latent macroeconomic uncertainty factor outperforms the VIX when forecasting volatility and jumps after the 2007 US Great Recession. We additionally find that latent macroeconomic uncertainty is a common forecasting factor of volatility and jumps of the intraday returns of S&P 500 constituents and has higher predictive power on the volatility and jumps of the equities which belong to the financial sector. Overall, our empirical analysis shows that stock market volatility is significantly affected by the rising degree of unpredictability in the macroeconomy, while it is relatively immune to shocks in observable uncertainty proxies.

Suggested Citation

  • Megaritis, Anastasios & Vlastakis, Nikolaos & Triantafyllou, Athanasios, 2020. "Stock market volatility and jumps in times of uncertainty," Essex Finance Centre Working Papers 29200, University of Essex, Essex Business School.
  • Handle: RePEc:esy:uefcwp:29200
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    Cited by:

    1. Peng-Fei Dai & Xiong Xiong & Zhifeng Liu & Toan Luu Duc Huynh & Jianjun Sun, 2021. "Preventing crash in stock market: The role of economic policy uncertainty during COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-15, December.
    2. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    3. Arafet Farroukh & Martina Metzger & Hela Mzoughi, 2025. "Assessing the influence of cryptocurrencies on financial market stability," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 15(2), pages 425-472, June.
    4. Grobys, Klaus & Huynh, Toan Luu Duc, 2022. "When Tether says “JUMP!” Bitcoin asks “How low?”," Finance Research Letters, Elsevier, vol. 47(PA).
    5. Xue Gong & Weiguo Zhang & Weijun Xu & Zhe Li, 2022. "Uncertainty index and stock volatility prediction: evidence from international markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-44, December.
    6. Lu Yang, 2025. "From Economic Policy Uncertainty to Implied Market Volatility: Nothing to Fear?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(2), pages 143-157, February.
    7. Khalfaoui, Rabeh & Stef, Nicolae & Wissal, Ben Arfi & Sami, Ben Jabeur, 2022. "Dynamic spillover effects and connectedness among climate change, technological innovation, and uncertainty: Evidence from a quantile VAR network and wavelet coherence," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    8. Masoud Ataei, 2025. "Multiscale Causal Analysis of Market Efficiency via News Uncertainty Networks and the Financial Chaos Index," Papers 2505.01543, arXiv.org.
    9. Hitz, Lukas & Mustafi, Ismail H. & Zimmermann, Heinz, 2022. "The pricing of volatility risk in the US equity market," International Review of Financial Analysis, Elsevier, vol. 79(C).
    10. Martina Halouskov'a & v{S}tefan Ly'ocsa, 2025. "Forecasting U.S. equity market volatility with attention and sentiment to the economy," Papers 2503.19767, arXiv.org.
    11. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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