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	0.7145	0.10
αARCH	0.2605	0.00
βGARCH	0.7395	0.00

γ₁	-4.7025	0.00
γ₂	5.8891	0.00
γ₃	5.9269	0.00
γ₄	13.4067	0.05
γ₅	-59.7493	0.00
γ₆	61.1213	0.00
γ₇	-27.1373	0.00
γ₈	10.6181	0.00

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.7145	0.10
α ARCH Response to squared shocks	0.2605	0.00
β GARCH Volatility persistence	0.7395	0.00

γ₁	-4.7025	0.00
γ₂	5.8891	0.00
γ₃	5.9269	0.00
γ₄	13.4067	0.05
γ₅	-59.7493	0.00
γ₆	61.1213	0.00
γ₇	-27.1373	0.00
γ₈	10.6181	0.00

V-Lab

Ex-pack Corrugated Cartons Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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