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	20.6522	4.07***
αARCH	0.2142	6.19***
βGARCH	0.7764	24.05***

γ₁	-0.5416	-0.75
γ₂	2.4003	1.63
γ₃	-2.6664	-1.91*
γ₄	0.5104	0.56
γ₅	1.0234	1.21
γ₆	-1.1046	-1.58
γ₇	1.0409	1.58
γ₈	-0.9473	-1.15
γ₉	0.7263	0.71
γ₁₀	-5.9962	-2.00**

Parameter	Value	t-statistic
ω const Unconditional variance weight	20.6522	4.07***
α ARCH Response to squared shocks	0.2142	6.19***
β GARCH Volatility persistence	0.7764	24.05***

γ₁	-0.5416	-0.75
γ₂	2.4003	1.63
γ₃	-2.6664	-1.91*
γ₄	0.5104	0.56
γ₅	1.0234	1.21
γ₆	-1.1046	-1.58
γ₇	1.0409	1.58
γ₈	-0.9473	-1.15
γ₉	0.7263	0.71
γ₁₀	-5.9962	-2.00**

V-Lab

Value Convergence Holdings Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Value Convergence Holdings Ltd Analyses