Quantifying the cross-correlations between online searches and Bitcoin market

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.