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	1.1435	5.91***
αARCH	0.1262	4.86***
βGARCH	0.7203	16.13***

γ₁	-0.8512	-2.76***
γ₂	0.3733	0.74
γ₃	1.0993	3.27***
γ₄	-0.4617	-2.21**
γ₅	-0.3585	-2.33**
γ₆	0.3190	2.12**
γ₇	-0.3074	-1.82*
γ₈	0.5706	3.15***
γ₉	-0.8367	-3.87***
γ₁₀	0.7264	2.12**

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1435	5.91***
α ARCH Response to squared shocks	0.1262	4.86***
β GARCH Volatility persistence	0.7203	16.13***

γ₁	-0.8512	-2.76***
γ₂	0.3733	0.74
γ₃	1.0993	3.27***
γ₄	-0.4617	-2.21**
γ₅	-0.3585	-2.33**
γ₆	0.3190	2.12**
γ₇	-0.3074	-1.82*
γ₈	0.5706	3.15***
γ₉	-0.8367	-3.87***
γ₁₀	0.7264	2.12**

V-Lab

Cadence Capital Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Cadence Capital Ltd Analyses