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	1.2279	2.12**
αARCH	0.1659	3.93***
βGARCH	0.8338	19.65***

γ₁	1.1076	1.32
γ₂	-7.6518	-1.98**
γ₃	17.4638	1.91*
γ₄	-14.9878	-1.60
γ₅	1.0434	0.25
γ₆	5.6426	3.89***
γ₇	-4.4474	-5.15***
γ₈	3.5581	4.95***
γ₉	-2.4818	-3.55***
γ₁₀	0.7734	0.91

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.2279	2.12**
α ARCH Response to squared shocks	0.1659	3.93***
β GARCH Volatility persistence	0.8338	19.65***

γ₁	1.1076	1.32
γ₂	-7.6518	-1.98**
γ₃	17.4638	1.91*
γ₄	-14.9878	-1.60
γ₅	1.0434	0.25
γ₆	5.6426	3.89***
γ₇	-4.4474	-5.15***
γ₈	3.5581	4.95***
γ₉	-2.4818	-3.55***
γ₁₀	0.7734	0.91

V-Lab

Volex PLC Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Volex PLC Analyses