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	0.6591	3.64***
αARCH	0.1721	12.75***
βGARCH	0.7929	50.28***

γ₁	-0.3189	-2.55**
γ₂	0.7098	4.08***
γ₃	-0.8659	-8.66***
γ₄	1.0074	11.05***
γ₅	-1.0200	-11.24***
γ₆	0.7334	7.91***
γ₇	-0.5869	-5.92***
γ₈	0.7612	7.56***
γ₉	-0.5545	-5.40***
γ₁₀	0.1610	0.99

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.6591	3.64***
α ARCH Response to squared shocks	0.1721	12.75***
β GARCH Volatility persistence	0.7929	50.28***

γ₁	-0.3189	-2.55**
γ₂	0.7098	4.08***
γ₃	-0.8659	-8.66***
γ₄	1.0074	11.05***
γ₅	-1.0200	-11.24***
γ₆	0.7334	7.91***
γ₇	-0.5869	-5.92***
γ₈	0.7612	7.56***
γ₉	-0.5545	-5.40***
γ₁₀	0.1610	0.99

V-Lab

Creo Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Creo Co Ltd Analyses