How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

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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	3.1284	2.59***
αARCH	0.1087	10.86***
βGARCH	0.8769	58.73***

γ₁	-0.0801	-0.70
γ₂	-0.0902	-0.59
γ₃	0.5190	5.36***
γ₄	-0.6077	-7.38***
γ₅	0.3235	4.22***
γ₆	0.0065	0.09
γ₇	-0.0464	-0.75
γ₈	-0.1410	-1.55

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.1284	2.59***
α ARCH Response to squared shocks	0.1087	10.86***
β GARCH Volatility persistence	0.8769	58.73***

γ₁	-0.0801	-0.70
γ₂	-0.0902	-0.59
γ₃	0.5190	5.36***
γ₄	-0.6077	-7.38***
γ₅	0.3235	4.22***
γ₆	0.0065	0.09
γ₇	-0.0464	-0.75
γ₈	-0.1410	-1.55

V-Lab

CIE Automotive SA Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other CIE Automotive SA Analyses