How volatility evolves over time

How illiquidity evolves over time

{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

Spline Coefficients

Value at Risk (VaR) estimates the maximum loss at a given confidence level. Expected Shortfall (ES) estimates the average loss beyond VaR.

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Param	Value	t-stat
ωconst	1.5471	2.10**
αARCH	0.2031	7.00***
βGARCH	0.7966	27.43***

γ₁	0.4440	3.04***
γ₂	-2.1712	-5.92***
γ₃	1.2469	0.58
γ₄	5.1614	0.78
γ₅	-10.2533	-1.29
γ₆	7.5724	1.49
γ₇	-0.1650	-0.05
γ₈	-1.2641	-0.52
γ₉	-3.7737	-1.55

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.5471	2.10**
α ARCH Response to squared shocks	0.2031	7.00***
β GARCH Volatility persistence	0.7966	27.43***

γ₁	0.4440	3.04***
γ₂	-2.1712	-5.92***
γ₃	1.2469	0.58
γ₄	5.1614	0.78
γ₅	-10.2533	-1.29
γ₆	7.5724	1.49
γ₇	-0.1650	-0.05
γ₈	-1.2641	-0.52
γ₉	-3.7737	-1.55

V-Lab

Shenzhen Zhongheng Huafa Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Shenzhen Zhongheng Huafa Co Ltd Analyses