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Orthogonalized impulse response diagram (response variable: Bitcoin)

Orthogonalized impulse response diagram (response variable: Bitcoin)

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To analyze the asset attribute and hedge effect of Bitcoin, we investigate the relationship between Bitcoin and several kinds of traditional financial assets by the univariate GARCH and multivariate GARCH models. We find that Bitcoin has a unique risk-return characteristic and volatility clustering performance, its high volatility persistence simil...

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This paper attempts to understand the dynamic interrelationships and financial asset capabilities of Bitcoin by analysing several aspects of its volatility vis-a-vis other asset classes. This study aims to analyse the volatility dynamics of the returns of Bitcoin. An asymmetric GARCH model (EGARCH) is used to investigate whether Bitcoin may be usef...

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... The author shows that Bitcoin and stock market returns are positively correlated during financial market downturns, in sharp contrast to the behaviour of gold returns, which is widely believed to be a hedging instrument against stock market downfalls. These findings are challenged by (i) [6,7], who show that gold is very sensitive to uncertainty shock from cryptocurrency markets, and by (ii) [7], who employs a timevarying parameter vector autoregressive model to show that gold is vulnerable to return and volatility spillovers from cryptocurrency uncertainty measures. The difference in behaviour between Bitcoin and commodities returns is carried out also for higher-order moments. ...
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We use a robust measure of non-linear dependence, the Gerber cross-correlation statistic, to study the cross-dependence between the returns on Bitcoin and a set of commodities, namely wheat, gold, platinum and crude oil WTI. The Gerber statistic enables us to obtain a more robust co-movement measure since it is neither affected by extremely large nor small movements that characterise financial time series; thus, it strips out noise from the data and allows us to capture effective co-movements between series when the movements are “substantial”. Focusing on the period 2014–2022, we construct the bootstrapped confidence intervals for the Gerber statistic and test the null that all the Gerber cross-correlations up to lag kmax are zero. Our results indicate a low degree of dependence between Bitcoin and commodities prices, both when we consider contemporaneous correlation and when we employ correlations between current Bitcoin and lagged (one day, one week, or one month) commodities returns. Further, the cross-correlation between Bitcoin and commodities’ returns, although scanty, shows an increasing trend during periods of economic, health and financial turbulence. This increased cross-correlation of returns during hectic market periods could be due to the contagion effect of some markets by others, which could also explain the strong dependence across volatilities we detected. Based on our results, Bitcoin cannot be considered the “new digital gold”. Keywords: Gerber correlation; cross-correlation; comovements; Bitcoin