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	1.1003	1.40
αARCH	0.2594	5.91***
βGARCH	0.7384	17.10***

γ₁	0.4367	2.58***
γ₂	-1.1782	-3.70***
γ₃	1.3120	4.49***
γ₄	-0.6308	-1.51
γ₅	0.0748	0.10
γ₆	-0.5176	-0.63
γ₇	1.0875	2.39**
γ₈	-0.8283	-4.77***
γ₉	0.3800	3.28***
γ₁₀	-0.3791	-1.71*

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1003	1.40
α ARCH Response to squared shocks	0.2594	5.91***
β GARCH Volatility persistence	0.7384	17.10***

γ₁	0.4367	2.58***
γ₂	-1.1782	-3.70***
γ₃	1.3120	4.49***
γ₄	-0.6308	-1.51
γ₅	0.0748	0.10
γ₆	-0.5176	-0.63
γ₇	1.0875	2.39**
γ₈	-0.8283	-4.77***
γ₉	0.3800	3.28***
γ₁₀	-0.3791	-1.71*

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