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	0.7933	6.27***
αARCH	0.2649	4.90***
βGARCH	0.4630	7.98***

γ₁	-0.5188	-1.18
γ₂	0.7523	1.01
γ₃	-0.9943	-2.03**
γ₄	1.6197	4.89***
γ₅	-1.0922	-2.71***
γ₆	0.4997	1.29
γ₇	-1.4377	-4.52***
γ₈	2.0092	4.02***
γ₉	-1.1324	-2.15**

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.7933	6.27***
α ARCH Response to squared shocks	0.2649	4.90***
β GARCH Volatility persistence	0.4630	7.98***

γ₁	-0.5188	-1.18
γ₂	0.7523	1.01
γ₃	-0.9943	-2.03**
γ₄	1.6197	4.89***
γ₅	-1.0922	-2.71***
γ₆	0.4997	1.29
γ₇	-1.4377	-4.52***
γ₈	2.0092	4.02***
γ₉	-1.1324	-2.15**

V-Lab

CVC INCOME & GROWTH LTD Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other CVC INCOME & GROWTH LTD Analyses