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From pandemic to financial contagion: High-frequency risk metrics and Bayesian volatility analysis

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  • Davidovic, Milivoje

Abstract

This is an event-based study that uses intraday (hourly) log returns to quantify Conditional Value-at-Risk (CVaR) and MCMC stochastic volatility before and during the Covid-19 pandemic (January 2019–June 2020) across the stock, commodity and cryptocurrency markets. The results indicate pandemic-induced risk exposure (expected shortfall), increasing volatility, and stronger cross-market integration. These effects might reduce the potential benefits of cross-market hedging and contribute to a global financial contagion, imposing an additional constraint on both the bank-level risk management strategy and macroprudential policy framework. Thus, the ongoing crisis can be amplified through the global financial spillovers.

Suggested Citation

  • Davidovic, Milivoje, 2021. "From pandemic to financial contagion: High-frequency risk metrics and Bayesian volatility analysis," Finance Research Letters, Elsevier, vol. 42(C).
    • Handle: RePEc:eee:finlet:v:42:y:2021:i:c:s154461232031727x
    DOI: 10.1016/j.frl.2020.101913
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    References listed on IDEAS

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    Cited by:

    1. Escribano, Ana & Koczar, Monika W. & Jareño, Francisco & Esparcia, Carlos, 2023. "Shock transmission between crude oil prices and stock markets," Resources Policy, Elsevier, vol. 83(C).
    2. Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    3. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    4. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    5. Iyer, Subramanian Rama & Simkins, Betty J., 2022. "COVID-19 and the Economy: Summary of research and future directions," Finance Research Letters, Elsevier, vol. 47(PB).
    6. Liu, Yuntong & Wei, Yu & Wang, Qian & Liu, Yi, 2022. "International stock market risk contagion during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    7. Papathanasiou, Spyros & Dokas, Ioannis & Koutsokostas, Drosos, 2022. "Value investing versus other investment strategies: A volatility spillover approach and portfolio hedging strategies for investors," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    8. Huang, Linxian, 2024. "The relationship between cryptocurrencies and convention financial market: Dynamic causality test and time-varying influence," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 811-826.
    9. Yakup Arı, 2022. "TVP-VAR Based CARR-Volatility Connectedness: Evidence from The Russian-Ukraine Conflict," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 7(3), pages 590-607.
    10. Zhang, Yi & Zhou, Long & Chen, Yajiao & Liu, Fang, 2022. "The contagion effect of jump risk across Asian stock markets during the Covid-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).

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    More about this item

    Keywords

    COVID-19 and Financial Markets; Conditional VaR; MCMC Volatility; JEL Code: G15; G18; G41;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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