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Cryptocurrencies, Mainstream Asset Classes and Risk Factors - A Study of Connectedness

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  • George Milunovich

Abstract

We investigate connectedness within and across two major groups or assets: i) five popular cryptocurrencies, and ii) six major asset classes plus two commonly employed risk factors. Granger-causality tests uncover six direct channels of causality from the elements of the mainstream assets/risk factors group to digital assets. On the other hand there are two statistically significant causal links going in the other direction. In order to provide some perspective on the magnitude of the uncovered linkages we supplement the analysis by estimating networks from forecast error variance decompositions. The estimated connectedness within the groups is relatively large, whereas the linkages across the two groups are small in comparison. Namely, less than 2.2 percent of future uncertainty of any cryptocurrency is sourced from all non-crypto assets combined, while the joint contribution of all digital assets to non-crypto uncertainty does not exceed 1.5 percent.

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  • George Milunovich, 2018. "Cryptocurrencies, Mainstream Asset Classes and Risk Factors - A Study of Connectedness," Papers 1809.03072, arXiv.org.
  • Handle: RePEc:arx:papers:1809.03072
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    Cited by:

    1. Victoria Dobrynskaya & Mikhail Dubrovskiy, 2022. "Cryptocurrencies Meet Equities: Risk Factors And Asset Pricing Relationships," HSE Working papers WP BRP 86/FE/2022, National Research University Higher School of Economics.
    2. Cameron Cornell & Lewis Mitchell & Matthew Roughan, 2023. "Vector Autoregression in Cryptocurrency Markets: Unraveling Complex Causal Networks," Papers 2308.15769, arXiv.org.
    3. Cameron Cornell & Lewis Mitchell & Matthew Roughan, 2024. "Enhancing Causal Discovery in Financial Networks with Piecewise Quantile Regression," Papers 2408.12210, arXiv.org.
    4. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    5. Shahzad, Syed Jawad Hussain & Balli, Faruk & Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad, 2022. "Do conventional currencies hedge cryptocurrencies?," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 223-228.
    6. Guizhou Wang & Kjell Hausken, 2022. "Competition between Variable–Supply and Fixed–Supply Currencies," Economies, MDPI, vol. 10(11), pages 1-20, October.
    7. Zaremba, Adam & Cakici, Nusret & Demir, Ender & Long, Huaigang, 2022. "When bad news is good news: Geopolitical risk and the cross-section of emerging market stock returns," Journal of Financial Stability, Elsevier, vol. 58(C).
    8. Milunovich, George, 2022. "Assessing the connectedness between Proof of Work and Proof of Stake/Other digital coins," Economics Letters, Elsevier, vol. 211(C).
    9. Guizhou Wang & Kjell Hausken, 2022. "The evolution of fixed-supply and variable-supply currencies," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    10. Diana Barro & Antonella Basso & Stefania Funari & Guglielmo Alessandro Visentin, 2024. "The Effects of the Introduction of Volume-Based Liquidity Constraints in Portfolio Optimization with Alternative Investments," Mathematics, MDPI, vol. 12(15), pages 1-26, August.

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