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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	56
αARCH	0.0186	2.70***
βGARCH	0.8694	57.66***
γleverage	0.0815	6.11***
λ₁tau intercept	0.0092	1.69*
λ₂forecast adj.	0.0251	2.89***
λ₃tau persistence	0.9719	101.56***

Parameter	Value	t-statistic
m window Rolling window length	56
α ARCH Response to squared shocks	0.0186	2.70***
β GARCH Volatility persistence	0.8694	57.66***
γ leverage Additional response to negative shocks	0.0815	6.11***
λ₁ tau intercept Baseline long-term coefficient	0.0092	1.69*
λ₂ forecast adj. Forecast performance sensitivity	0.0251	2.89***
λ₃ tau persistence Long-term factor persistence	0.9719	101.56***

V-Lab

Siemens AG MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Siemens AG Analyses