Pattern and determinants of tail-risk transmission between cryptocurrency markets: new evidence from recent crisis episodes

Aktham Maghyereh, Salem Adel Ziadat

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)

    Abstract

    The main objective of this study is to investigate tail risk connectedness among six major cryptocurrency markets and determine the extent to which investor sentiment, economic conditions, and economic uncertainty can predict tail risk interconnectedness. Combining the Conditional Autoregressive Value-at-Risk (CAViaR) model with the time-varying parameter vector autoregressive (TVP-VAR) approach shows that the transmission of tail risks among cryptocurrencies changes dynamically over time. During crises and significant events, transmission bursts and tail risks change. Based on both in- and out-of-sample forecasts, we find that the information contained in investor sentiment, economic conditions, and uncertainty includes significant predictive content about the tail risk connectedness of cryptocurrencies.

    Original languageEnglish
    Article number77
    JournalFinancial Innovation
    Volume10
    Issue number1
    DOIs
    Publication statusPublished - Dec 2024

    Keywords

    • C53
    • CAViaR
    • Cryptocurrency
    • G1
    • G32
    • G41
    • Predictability
    • Tail-risk connectedness
    • TVP-VAR

    ASJC Scopus subject areas

    • Finance
    • Management of Technology and Innovation

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