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	1.4595	4.63***
αARCH	0.2390	5.75***
βGARCH	0.7588	18.96***

γ₁	0.2064	0.05
γ₂	-0.6080	-0.13
γ₃	-6.2366	-1.63
γ₄	21.7972	2.74***
γ₅	-23.4817	-3.17***
γ₆	7.2061	2.51**
γ₇	3.1695	2.33**
γ₈	-3.7953	-2.44**
γ₉	0.7584	0.44
γ₁₀	6.7857	3.75***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.4595	4.63***
α ARCH Response to squared shocks	0.2390	5.75***
β GARCH Volatility persistence	0.7588	18.96***

γ₁	0.2064	0.05
γ₂	-0.6080	-0.13
γ₃	-6.2366	-1.63
γ₄	21.7972	2.74***
γ₅	-23.4817	-3.17***
γ₆	7.2061	2.51**
γ₇	3.1695	2.33**
γ₈	-3.7953	-2.44**
γ₉	0.7584	0.44
γ₁₀	6.7857	3.75***

V-Lab

Virtual Mind Holding Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Virtual Mind Holding Co Ltd Analyses