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	1.3789	4.30***
αARCH	0.2430	5.67***
βGARCH	0.7543	18.64***

γ₁	0.1646	0.05
γ₂	-0.4957	-0.11
γ₃	-6.7670	-1.77*
γ₄	23.1469	2.83***
γ₅	-24.9220	-3.24***
γ₆	7.8951	2.65***
γ₇	2.9820	2.30**
γ₈	-3.8084	-2.54**
γ₉	0.9237	0.54
γ₁₀	6.9850	3.90***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3789	4.30***
α ARCH Response to squared shocks	0.2430	5.67***
β GARCH Volatility persistence	0.7543	18.64***

γ₁	0.1646	0.05
γ₂	-0.4957	-0.11
γ₃	-6.7670	-1.77*
γ₄	23.1469	2.83***
γ₅	-24.9220	-3.24***
γ₆	7.8951	2.65***
γ₇	2.9820	2.30**
γ₈	-3.8084	-2.54**
γ₉	0.9237	0.54
γ₁₀	6.9850	3.90***

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