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	2.1434	2.29**
αARCH	0.1631	5.86***
βGARCH	0.8175	34.85***

γ₁	0.8392	2.02**
γ₂	-2.0852	-2.53**
γ₃	2.0408	2.73***
γ₄	-0.9885	-2.01**
γ₅	0.4213	1.59
γ₆	-0.2465	-1.29
γ₇	-0.0177	-0.12
γ₈	-0.0086	-0.05
γ₉	0.1592	0.70

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.1434	2.29**
α ARCH Response to squared shocks	0.1631	5.86***
β GARCH Volatility persistence	0.8175	34.85***

γ₁	0.8392	2.02**
γ₂	-2.0852	-2.53**
γ₃	2.0408	2.73***
γ₄	-0.9885	-2.01**
γ₅	0.4213	1.59
γ₆	-0.2465	-1.29
γ₇	-0.0177	-0.12
γ₈	-0.0086	-0.05
γ₉	0.1592	0.70

V-Lab

Eurocash Sa Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Eurocash Sa Analyses