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How volatility evolves over time

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{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	61
αARCH	0.0362	3.25***
βGARCH	0.7221	15.52***
γleverage	0.1080	4.24***
λ₁tau intercept	0.7186	2.96***
λ₂forecast adj.	0.7997	3.71***
λ₃tau persistence	0.0000	0.00

Parameter	Value	t-statistic
m window Rolling window length	61
α ARCH Response to squared shocks	0.0362	3.25***
β GARCH Volatility persistence	0.7221	15.52***
γ leverage Additional response to negative shocks	0.1080	4.24***
λ₁ tau intercept Baseline long-term coefficient	0.7186	2.96***
λ₂ forecast adj. Forecast performance sensitivity	0.7997	3.71***
λ₃ tau persistence Long-term factor persistence	0.0000	0.00

V-Lab

Fresenius SE & Co KGaA MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Fresenius SE & Co KGaA Analyses