Quantifying the cross-correlations between online searches and Bitcoin market
Xiao Li and
Dehua Shen ()
Physica A: Statistical Mechanics and its Applications, 2018, vol. 509, issue C, 657-672
In this paper, we quantify the cross-correlations between Google Trends and Bitcoin market. By employing the Multifractal Detrended Cross-correlation Analysis (MF-DCCA) method, we find that the change of Google Trends (CGT) and Bitcoin market, i.e., returns and changes of volume, are overall significantly cross-correlated based on the cross-correlation test. In particular, the empirical results show that: (1) there exist power-law cross-correlations between CGT and Bitcoin returns as well as CGT and changes of volume; (2) the cross-correlations between CGT and returns have a higher degree of multifractal in the long-term and weak multifractal in the short-term, while the cross-correlations between CGT and change of volume show the opposite trend. (3) with the rolling window analysis, we further find that there is a decrease trend for the cross-correlations between CGT and Bitcoin returns over time, and the cross-correlations scaling exponents are less than 0.5, which indicate that they are both anti-persistent cross-correlated.
Keywords: Google Trends; Bitcoin; Cross-correlations; Multifractal detrended cross-correlation analysis; Rolling windows analysis (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:509:y:2018:i:c:p:657-672
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