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	3.4610	2.30**
αARCH	0.2791	5.18***
βGARCH	0.7180	13.49***

γ₁	0.4365	2.65***
γ₂	-1.1973	-3.91***
γ₃	1.4269	5.26***
γ₄	-1.2164	-4.99***
γ₅	0.9006	3.13***
γ₆	0.2161	0.28
γ₇	-5.3890	-1.58
γ₈	12.9941	1.75*
γ₉	-12.2660	-1.80*
γ₁₀	4.3708	1.96**

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.4610	2.30**
α ARCH Response to squared shocks	0.2791	5.18***
β GARCH Volatility persistence	0.7180	13.49***

γ₁	0.4365	2.65***
γ₂	-1.1973	-3.91***
γ₃	1.4269	5.26***
γ₄	-1.2164	-4.99***
γ₅	0.9006	3.13***
γ₆	0.2161	0.28
γ₇	-5.3890	-1.58
γ₈	12.9941	1.75*
γ₉	-12.2660	-1.80*
γ₁₀	4.3708	1.96**

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