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	0.3153	2.84***
αARCH	0.1049	7.95***
βGARCH	0.8229	38.15***

γ₁	-0.0294	-0.23
γ₂	-0.1651	-0.91
γ₃	0.4298	4.37***
γ₄	-0.4940	-7.00***
γ₅	0.3934	6.03***
γ₆	-0.2012	-3.31***
γ₇	0.1489	2.71***
γ₈	-0.1480	-2.58***
γ₉	0.1105	1.83*
γ₁₀	-0.0488	-0.74

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.3153	2.84***
α ARCH Response to squared shocks	0.1049	7.95***
β GARCH Volatility persistence	0.8229	38.15***

γ₁	-0.0294	-0.23
γ₂	-0.1651	-0.91
γ₃	0.4298	4.37***
γ₄	-0.4940	-7.00***
γ₅	0.3934	6.03***
γ₆	-0.2012	-3.31***
γ₇	0.1489	2.71***
γ₈	-0.1480	-2.58***
γ₉	0.1105	1.83*
γ₁₀	-0.0488	-0.74

V-Lab

UBS (CH) Property Fund - Swiss Commercial Interswiss Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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