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	1.3079	2.43**
αARCH	0.2165	10.52***
βGARCH	0.7832	37.93***

γ₁	0.0025	0.02
γ₂	-1.0659	-5.12***
γ₃	3.0925	8.11***
γ₄	-4.3023	-7.27***
γ₅	1.6656	1.64
γ₆	2.9420	1.53
γ₇	-0.7757	-0.42
γ₈	-5.0855	-1.75*

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3079	2.43**
α ARCH Response to squared shocks	0.2165	10.52***
β GARCH Volatility persistence	0.7832	37.93***

γ₁	0.0025	0.02
γ₂	-1.0659	-5.12***
γ₃	3.0925	8.11***
γ₄	-4.3023	-7.27***
γ₅	1.6656	1.64
γ₆	2.9420	1.53
γ₇	-0.7757	-0.42
γ₈	-5.0855	-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