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Asymmetric network connectedness of fears

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  • Baruník, Jozef
  • Bevilacqua, Mattia
  • Tunaru, Radu

Abstract

This paper introduces forward-looking measures of the network connectedness of fears in the financial system, arising due to the good and bad beliefs of market participants about uncertainty that spreads unequally across a network of banks. We argue that this asymmetric network structure extracted from call and put traded option prices of the main U.S. banks contains valuable information for predicting macroeconomic conditions and economic uncertainty, and it can serve as a tool for forward-looking systemic risk monitoring.

Suggested Citation

  • Baruník, Jozef & Bevilacqua, Mattia & Tunaru, Radu, 2022. "Asymmetric network connectedness of fears," LSE Research Online Documents on Economics 108199, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:108199
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    Cited by:

    1. Timo Dimitriadis & Yannick Hoga, 2023. "Regressions under Adverse Conditions," Papers 2311.13327, arXiv.org.
    2. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2020. "Options-based systemic risk, financial distress, and macroeconomic downturns," LSE Research Online Documents on Economics 118850, London School of Economics and Political Science, LSE Library.
    3. Baruník, Jozef & Bevilacqua, Mattia & Faff, Robert, 2024. "Dynamic industry uncertainty networks and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    4. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," LSE Research Online Documents on Economics 119289, London School of Economics and Political Science, LSE Library.
    5. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    6. Naeem, Muhammad Abubakr & Lucey, Brian M. & Karim, Sitara & Ghafoor, Abdul, 2022. "Do financial volatilities mitigate the risk of cryptocurrency indexes?," Finance Research Letters, Elsevier, vol. 50(C).
    7. Jozef Barunik & Mattia Bevilacqua & Michael Ellington, 2023. "Common Firm-level Investor Fears: Evidence from Equity Options," Papers 2309.03968, arXiv.org.
    8. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    9. Yarovaya, Larisa & Brzeszczyński, Janusz & Goodell, John W. & Lucey, Brian & Lau, Chi Keung Marco, 2022. "Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    10. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    11. Muhammad Abubakr Naeem & Mudassar Hasan & Abraham Agyemang & Md Iftekhar Hasan Chowdhury & Faruk Balli, 2023. "Time‐frequency dynamics between fear connectedness of stocks and alternative assets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2188-2201, April.
    12. Li, Qiang & Nong, Huifu, 2022. "A closer look at Chinese housing market: Measuring intra-city submarket connectedness in Shanghai and Guangzhou," China Economic Review, Elsevier, vol. 74(C).
    13. Pagnottoni, Paolo & Spelta, Alessandro, 2023. "The motifs of risk transmission in multivariate time series: Application to commodity prices," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    14. Ye, Liping & Geng, Jiang-Bo, 2021. "Measuring the connectedness of global health sector stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    15. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," Journal of Financial Markets, Elsevier, vol. 65(C).

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    Keywords

    ES/K002309/1; ES/R009724/1;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • J1 - Labor and Demographic Economics - - Demographic Economics

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