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

Table 4

Relationship between algorithmic trading and liquidity indicators (September 7, 2015–December 31, 2015, excluding opening and closing time windows).

Model 1				Model 2
	0.0651		0.6159		0.3095		−0.7202
Panel A: contemporaneous variables
	−0.1405		−0.0928		−0.0157		−2.2388
Panel B: autoregressive lagged variables
	0.5563		0.6350		0.5653		0.2318
	0.1956		−0.0413		0.2185		0.1695
	0.1648		0.1945		0.1528		0.0814
Panel C: cross effect of lagged variables
	0.1643		0.0332		0.0094		1.5264
	0.0582		0.0154		0.0098		0.6386
	0.0257		0.0404		0.0028		0.3712
Panel D: control variables
	−0.0312		0.0291		−0.0220		1.0666
	−0.2917		−0.2738		−0.3589		1.8179
Model 3				Model 4
	0.1261		0.0242		0.3069		−0.7350
Panel A: contemporaneous variables
	−1.5548		−0.0069		−0.0157		−2.2388
Panel B: autoregressive lagged variables
	0.5478		0.6694		0.5653		0.2319
	0.1894		−0.0705		0.2183		0.1694
	0.1598		0.2118		0.1529		0.0816
Panel C: cross effect of lagged variables
	1.9926		0.0047		0.0094		1.5239
	0.7224		0.0015		0.0098		0.6369
	0.4966		0.0033		0.0028		0.3732
Panel D: control variables
	−0.0307		0.0018		−0.0220		1.0658
	−0.4101		−0.0069		−0.3589		1.8174

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