Quantifying the Cross-Correlations between Online Market Participation Willingness and Stock Market Dynamics

Table 1

Summary statistics.


	Mean	Std. dev.	Skew.	Kurt.	Max	Min

(A) Yu’e Bao Sentiment Index
	1033.156	290.028	1.555	7.505	2743.41	415.1
	0.00754	0.0457	1.169	7.064	1.284	−0.563

(B) Chinese stock market return
SSE50	0.000266	0.00709	−0.839	10.336	0.0328	−0.0428
CSI300	0.000261	0.00691	−1.189	10.062	0.0282	−0.0398
SME	0.000211	0.00789	−1.042	7.507	0.0287	−0.0382
GEM	0.000165	0.00934	−0.669	5.835	0.0301	−0.0405

(C) Chinese stock market trade volume
SSE50	0.0339	0.461	1.521	6.315	2.528	−0.752
CSI300	0.0254	0.351	1.189	5.257	1.968	−0.705
SME	0.0222	0.219	0.407	3.462	0.931	−0.758
GEM	0.0358	0.232	0.448	3.343	0.819	−0.767

(D) Chinese stock market volatility
SSE50	0.000276	0.000362	2.506	9.999	0.00221	0.0000259
CSI300	0.000261	0.000343	2.441	9.240	0.00195	0.0000249
SME	0.000321	0.000331	1.819	5.489	0.00152	0.0000605
GEM	0.0004502	0.000439	1.659	4.928	0.00204	0.0000908

This table reports the mean, standard deviation (Std. dev.), skewness (Skew.), kurtosis (Kurt.), minimum (Min), and maximum (Max) of Yu’e Bao Sentiment Index ( and ), the return, volume, and volatility for four stock market indices: SSE50, CSI300, SME, and GEM. The sample period extends from May 5, 2014, through May 10, 2018.

Complexity

Quantifying the Cross-Correlations between Online Market Participation Willingness and Stock Market Dynamics

Table 1