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	0.9589	3.48***
αARCH	0.1011	1.48
βGARCH	0.0846	0.28

γ₁	9.4290	2.83***
γ₂	-11.3936	-1.98**
γ₃	-6.4080	-1.14
γ₄	19.0482	3.83***
γ₅	-17.1211	-4.33***
γ₆	9.0059	1.70*
γ₇	-12.9424	-1.30

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.9589	3.48***
α ARCH Response to squared shocks	0.1011	1.48
β GARCH Volatility persistence	0.0846	0.28

γ₁	9.4290	2.83***
γ₂	-11.3936	-1.98**
γ₃	-6.4080	-1.14
γ₄	19.0482	3.83***
γ₅	-17.1211	-4.33***
γ₆	9.0059	1.70*
γ₇	-12.9424	-1.30

V-Lab

CEPS PLC Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other CEPS PLC Analyses