We investigate the cross-correlations of return-volume relationship of the Bitcoin market. In particular, we select eight exchange rates whose trading volume accounts for more than 98% market shares to synthesize Bitcoin indexes. The empirical results based on multifractal detrended cross-correlation analysis reveal that the nonlinear dependencies and power-law cross-correlations in return-volume relationship are found; all cross-correlations are multifractal, and there are antipersistent behaviors of cross-correlation for q=2; the price of small fluctuations is more persistent than that of the volume, while (...) the volume of larger fluctuations is more antipersistent; and the rolling window method shows that the cross-correlations of return-volume are antipersistent in the entire sample period. (shrink)

In this paper, we employ Weibo Index as the proxy for investor attention and analyze the relationships between investor attention and stock market performance, i.e., trading volume, return, and volatility. The empirical results firstly show that Weibo attention is positively related to trading volume, intraday volatility, and return. Secondly, there exist bidirectional causal relationships between Weibo attention and stock market performance. Thirdly, we generally find that higher Weibo attention indicates higher correlation coefficients with the quantile regression analysis.