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	1.1671	3.64***
αARCH	0.0940	6.39***
βGARCH	0.8767	48.24***

γ₁	0.6541	2.59***
γ₂	-0.7266	-1.92*
γ₃	-0.1115	-0.39
γ₄	0.2947	0.96
γ₅	-0.3398	-1.22
γ₆	1.1931	3.49***
γ₇	-2.4235	-4.81***
γ₈	2.1144	3.17***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1671	3.64***
α ARCH Response to squared shocks	0.0940	6.39***
β GARCH Volatility persistence	0.8767	48.24***

γ₁	0.6541	2.59***
γ₂	-0.7266	-1.92*
γ₃	-0.1115	-0.39
γ₄	0.2947	0.96
γ₅	-0.3398	-1.22
γ₆	1.1931	3.49***
γ₇	-2.4235	-4.81***
γ₈	2.1144	3.17***

V-Lab

Imiter Ste Metallurgique Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Imiter Ste Metallurgique Analyses