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Time Varying Dependence in the Cryptocurrency Market and COVID 19 Panic Index: An Empirical Investigation

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  • Lamia Kalai

    (Department of Finance, Universit de Tunis El manar, Tunis, Tunisia.)

Abstract

The aim of this paper is to study the interdependence between the Coronavirus Panic Index (PI) and major cryptocurrencies throughout the period of the Covid-19 pandemic.We investigate the evolution of cryptocurrency s value following changes in the Covid panic index levels; then, we use the DCC-MIDAS specification to extract the long- and short-term volatility components of cryptocurrencies and study the responses of the cryptocurrencies to the pandemic panic index. The results show that the panic level metrics could be considered as a potential driver of cryptocurrencies volatility and has a significantly positive influence on the long-term cryptocurrencies correlation during stress levels. Our findings contribute to the existing literature in several ways. First ,we provide specific evidence on the driving effect of Covid panic index on cryptocurrencies correlation during a crisis. Second, our paper adds to the current literature on cryptocurrencies and fills in the existing gap related to the lack of academic research on the pandemic s impact on the cryptocurrency market. Third, the results offer interesting insights for future research and have important implications for investors, especially in understanding the cryptocurrencies behavior and exploring whether cryptocurrencies can serve as a hedge against the COVID-19 crisis.

Suggested Citation

  • Lamia Kalai, 2022. "Time Varying Dependence in the Cryptocurrency Market and COVID 19 Panic Index: An Empirical Investigation," International Journal of Economics and Financial Issues, Econjournals, vol. 12(2), pages 37-51, March.
    • Handle: RePEc:eco:journ1:2022-02-4
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Covid 19; Volatility; digital currency; DCC-MIDAS ; Kernel regression; response-impulsion; causality;
    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
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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