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	3.4653	2.30**
αARCH	0.2792	5.18***
βGARCH	0.7179	13.48***

γ₁	0.4364	2.65***
γ₂	-1.1971	-3.91***
γ₃	1.4267	5.26***
γ₄	-1.2163	-4.99***
γ₅	0.9005	3.13***
γ₆	0.2164	0.28
γ₇	-5.3904	-1.58
γ₈	12.9991	1.75*
γ₉	-12.2764	-1.80*
γ₁₀	4.3899	1.97**

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.4653	2.30**
α ARCH Response to squared shocks	0.2792	5.18***
β GARCH Volatility persistence	0.7179	13.48***

γ₁	0.4364	2.65***
γ₂	-1.1971	-3.91***
γ₃	1.4267	5.26***
γ₄	-1.2163	-4.99***
γ₅	0.9005	3.13***
γ₆	0.2164	0.28
γ₇	-5.3904	-1.58
γ₈	12.9991	1.75*
γ₉	-12.2764	-1.80*
γ₁₀	4.3899	1.97**

V-Lab

Shanghai Yaohua Pilkington Glass Group Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Shanghai Yaohua Pilkington Glass Group Co Ltd Analyses