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	1.3112	2.42**
αARCH	0.2166	10.56***
βGARCH	0.7830	38.03***

γ₁	0.0065	0.06
γ₂	-1.0747	-5.15***
γ₃	3.0978	8.05***
γ₄	-4.2784	-7.17***
γ₅	1.6085	1.58
γ₆	2.9517	1.54
γ₇	-0.6987	-0.37
γ₈	-5.1329	-1.75*

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3112	2.42**
α ARCH Response to squared shocks	0.2166	10.56***
β GARCH Volatility persistence	0.7830	38.03***

γ₁	0.0065	0.06
γ₂	-1.0747	-5.15***
γ₃	3.0978	8.05***
γ₄	-4.2784	-7.17***
γ₅	1.6085	1.58
γ₆	2.9517	1.54
γ₇	-0.6987	-0.37
γ₈	-5.1329	-1.75*

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