High-Frequency Trading and Its Impact on Exogenous Liquidity Risk of China’s Stock Index Futures Market before and after Trading Restrictions

Table 3

Relationship between algorithmic trading and liquidity indicators (July 1, 2014–May 31, 2016).

Model 1				Model 2
	0.2154		1.0475		0.1487		2.8018
Panel A: contemporaneous variables
	0.0236		0.0825		0.005		1.3549
Panel B: autoregressive lagged variables
	0.5215		0.6896		0.5214		0.2288
	0.1724		0.1126		0.1878		0.0439
	0.1648		0.1029		0.1598		0.1057
Panel C: cross effect of lagged variables
	−0.0103		−0.0747		−0.0004		−0.2771
	−0.0043		0.0319		0.0041		−0.4124
	−0.0015		0.0311		0.0022		−0.3044
Panel D: control variables
	−0.0251		0.0232		−0.0379		1.1059
	−0.4785		−0.4618		−0.4203		0.0059
Model 3				Model 4
	0.1171		0.0692		0.1383		1.8431
Panel A: contemporaneous variables
	0.1636		0.0032		−0.0055		−0.6859
Panel B: autoregressive lagged variables
	0.5201		0.6776		0.5372		0.2436
	0.1723		0.1199		0.1869		0.1019
	0.1544		0.1029		0.1600		0.0906
Panel C: cross effect of lagged variables
	0.0333		−0.0038		0.0069		0.9865
	0.0737		0.0036		0.0049		−0.1064
	−0.1213		0.0038		0.0024		0.3277
Panel D: control variables
	−0.0257		0.0017		−0.0307		1.1320
	−0.4324		−0.0237		−0.3814		0.7659

, , and Significant levels of 0.05, 0.01, and 0.001, respectively.