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	1.1286	6.23***
αARCH	0.1224	4.86***
βGARCH	0.7342	16.85***

γ₁	-0.9052	-4.56***
γ₂	0.6503	1.96*
γ₃	0.9255	3.61***
γ₄	-0.8457	-4.96***
γ₅	0.2600	2.28**
γ₆	-0.2782	-2.47**
γ₇	0.5262	4.53***
γ₈	-0.6750	-4.17***
γ₉	0.5364	2.05**

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1286	6.23***
α ARCH Response to squared shocks	0.1224	4.86***
β GARCH Volatility persistence	0.7342	16.85***

γ₁	-0.9052	-4.56***
γ₂	0.6503	1.96*
γ₃	0.9255	3.61***
γ₄	-0.8457	-4.96***
γ₅	0.2600	2.28**
γ₆	-0.2782	-2.47**
γ₇	0.5262	4.53***
γ₈	-0.6750	-4.17***
γ₉	0.5364	2.05**

V-Lab

Cadence Capital Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Cadence Capital Ltd Analyses