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Stock market and cryptocurrency market volatility

Author

Listed:
  • Manevich, Vyacheslav

    (NRU HSE, Moscow, Russian Federation)

  • Peresetsky, Anatoly

    (NRU HSE, Moscow, Russian Federation)

  • Pogorelova, Polina

    (NRU HSE, Moscow, Russian Federation)

Abstract

In the last ten years, cryptocurrencies have developed rapidly, of which bitcoin has the largest capitalization. With the development of the cryptocurrency market, more and more investors include bitcoin in their asset portfolio. In this regard, the question of the relationship between the volatility of the cryptocurrency market and the stock market is of particular interest. This article analyzes the common stochastic component of the realized volatility of bitcoin and e-mini S&P futures. The assessment of the global stochastic component and its share in the volatility of the S&P 500 futures and bitcoin in the rolling window made it possible to analyze the dynamics of the relationship between the realized volatility of these two assets, as well as put forward a hypothesis about the causes and preconditions for volatility flows between the cryptocurrency market and the stock market

Suggested Citation

  • Manevich, Vyacheslav & Peresetsky, Anatoly & Pogorelova, Polina, 2022. "Stock market and cryptocurrency market volatility," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 65-76.
    • Handle: RePEc:ris:apltrx:0439
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    References listed on IDEAS

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    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Cartea, Álvaro & Karyampas, Dimitrios, 2011. "Volatility and covariation of financial assets: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3319-3334.
    4. Xin Wang & Xi Chen & Peng Zhao, 2020. "The Relationship Between Bitcoin and Stock Market," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 11(2), pages 22-35, April.
    5. Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
    6. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    7. Uzonwanne, Godfrey, 2021. "Volatility and return spillovers between stock markets and cryptocurrencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 30-36.
    8. Mardi Dungey & Vance L Martin & Adrian R Pagan, 2000. "A multivariate latent factor decomposition of international bond yield spreads," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 697-715.
    9. Ahmed, Walid M.A., 2021. "Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    10. López-Cabarcos, M. Ángeles & Pérez-Pico, Ada M. & Piñeiro-Chousa, Juan & Šević, Aleksandar, 2021. "Bitcoin volatility, stock market and investor sentiment. Are they connected?," Finance Research Letters, Elsevier, vol. 38(C).
    11. Achraf Ghorbel & Ahmed Jeribi, 2021. "Investigating the relationship between volatilities of cryptocurrencies and other financial assets," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 817-843, December.
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    Cited by:

    1. Pogorelova, Polina, 2024. "Investigation of the impact of uncertainty indices on Bitcoin volatility using the ARDL model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 74, pages 35-50.

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    More about this item

    Keywords

    bitcoin; cryptocurrency; realized volatility; state–space model; S&P 500;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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