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
mwindow	31
αARCH	0.1098	6.23***
βGARCH	0.8755	37.30***
γleverage	-0.1098	-2.05**
λ₁tau intercept	0.4170	0.24
λ₂forecast adj.	0.0105	4.09***
λ₃tau persistence	0.9894	307.94***

Parameter	Value	t-statistic
m window Rolling window length	31
α ARCH Response to squared shocks	0.1098	6.23***
β GARCH Volatility persistence	0.8755	37.30***
γ leverage Additional response to negative shocks	-0.1098	-2.05**
λ₁ tau intercept Baseline long-term coefficient	0.4170	0.24
λ₂ forecast adj. Forecast performance sensitivity	0.0105	4.09***
λ₃ tau persistence Long-term factor persistence	0.9894	307.94***

V-Lab

Vienna Insurance Group AG Wiener Versicherung Gruppe ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Vienna Insurance Group AG Wiener Versicherung Gruppe Analyses