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Volatility Connectedness of Major Cryptocurrencies: The Role of Investor Happiness

Elie Bouri (), David Gabauer, Rangan Gupta () and Aviral Tiwari ()

No 202059, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper, we first obtain a time-varying measure of volatility connectedness involving fifteen major cryptocurrencies based on a dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model, and then analyze the role of investor sentiment in explaining the movement of the connectedness metric within a quantile-on-quantile framework. Our findings show that lower quantiles of investor happiness, built on Twitter feed data as a proxy for investor sentiment, is positively associated with the entire conditional distribution of connectedness, but the opposite is observed at higher values of investor happiness. In addition, when we look at the effect of sentiment on the common market volatility, we are able to deduce that as investors become exceedingly unhappy, overall market volatility increases and this is associated with high market connectedness. The heightened volatility possibly due to higher trading, seems to suggest that cryptocurrencies are used for hedging when investor sentiment is weak, with evidence in favor of this behavior being relatively stronger than the possible speculative motive associated with happy investors, as low total connectedness is coupled with high common volatility. Our results tend to suggest that, relatively more diversification opportunities are available when investors are happy rather than when sentiment is weak.

Keywords: Cryptocurrency Market; DCC-GARCH; Volatility Connectedness; Investor Happiness; Quantile-on-Quantile Regression (search for similar items in EconPapers)
JEL-codes: C22 C32 G10 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2020-06
New Economics Papers: this item is included in nep-ets, nep-fmk and nep-pay
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