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	0.5370	1.85*
αARCH	0.1025	10.74***
βGARCH	0.8724	74.23***

γ₁	0.1987	1.30
γ₂	-0.5376	-2.67***
γ₃	0.6140	7.61***
γ₄	-0.5303	-8.88***
γ₅	0.4374	6.66***
γ₆	-0.1866	-2.72***
γ₇	-0.1495	-2.18**
γ₈	0.3821	4.10***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.5370	1.85*
α ARCH Response to squared shocks	0.1025	10.74***
β GARCH Volatility persistence	0.8724	74.23***

γ₁	0.1987	1.30
γ₂	-0.5376	-2.67***
γ₃	0.6140	7.61***
γ₄	-0.5303	-8.88***
γ₅	0.4374	6.66***
γ₆	-0.1866	-2.72***
γ₇	-0.1495	-2.18**
γ₈	0.3821	4.10***

V-Lab

Kvk Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Kvk Corp Analyses