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

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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	0.7006	2.66***
αARCH	0.2145	4.65***
βGARCH	0.5645	4.83***

γ₁	-5.9328	-0.77
γ₂	6.2925	0.61
γ₃	-1.9499	-0.37
γ₄	6.8020	1.43
γ₅	-8.0237	-2.07**
γ₆	-0.8938	-0.27
γ₇	11.6017	2.41**
γ₈	-18.5447	-1.79*
γ₉	34.3160	2.01**
γ₁₀	-54.5098	-1.50

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.7006	2.66***
α ARCH Response to squared shocks	0.2145	4.65***
β GARCH Volatility persistence	0.5645	4.83***

γ₁	-5.9328	-0.77
γ₂	6.2925	0.61
γ₃	-1.9499	-0.37
γ₄	6.8020	1.43
γ₅	-8.0237	-2.07**
γ₆	-0.8938	-0.27
γ₇	11.6017	2.41**
γ₈	-18.5447	-1.79*
γ₉	34.3160	2.01**
γ₁₀	-54.5098	-1.50

V-Lab

Wintao Communications Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Wintao Communications Co Ltd Analyses