Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model

新冠疫情期间加密货币市场的关联性及推特的作用:来自平滑过渡回归模型的证据

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Abstract

Τhis paper presents new evidence on connectedness across cryptocurrencies in the era of the Covid-19 pandemic. The results from the TVP-VAR dynamic connectedness approach show that the degree of connectedness is time-varying, indicating a decline during the Covid-19 period. Next, this paper highlights the nonlinear characteristics of the relationship between connectedness and its explanatory variables. The results from the LSTR model indicate that the regression coefficients change smoothly between the low and the upper regimes as anxiety across Twitter users increases. As the latter changes smoothly from low to high values, the impact of higher Disease-based volatility or Twitter-based uncertainty on connectedness turns gradually from positive to negative. The upper regime is dominant during the Covid-19 pandemic. Important implications for investors and policy makers are derived.

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