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	3.6772	2.53**
αARCH	0.2726	5.36***
βGARCH	0.7249	14.40***

γ₁	0.4352	2.65***
γ₂	-1.1966	-3.92***
γ₃	1.4323	5.25***
γ₄	-1.2359	-4.98***
γ₅	0.9577	3.31***
γ₆	0.1084	0.14
γ₇	-5.5578	-1.51
γ₈	12.3245	1.69*
γ₉	-8.7510	-1.80*
γ₁₀	0.4166	0.39

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.6772	2.53**
α ARCH Response to squared shocks	0.2726	5.36***
β GARCH Volatility persistence	0.7249	14.40***

γ₁	0.4352	2.65***
γ₂	-1.1966	-3.92***
γ₃	1.4323	5.25***
γ₄	-1.2359	-4.98***
γ₅	0.9577	3.31***
γ₆	0.1084	0.14
γ₇	-5.5578	-1.51
γ₈	12.3245	1.69*
γ₉	-8.7510	-1.80*
γ₁₀	0.4166	0.39

V-Lab

Shanghai Yaohua Pilkington Glass Group Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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