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How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

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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	76
αARCH	0.0529	4.48***
βGARCH	0.8289	40.43***
γleverage	0.0685	3.27***
λ₁tau intercept	0.0161	1.58
λ₂forecast adj.	0.0364	2.66***
λ₃tau persistence	0.9616	66.37***

Parameter	Value	t-statistic
m window Rolling window length	76
α ARCH Response to squared shocks	0.0529	4.48***
β GARCH Volatility persistence	0.8289	40.43***
γ leverage Additional response to negative shocks	0.0685	3.27***
λ₁ tau intercept Baseline long-term coefficient	0.0161	1.58
λ₂ forecast adj. Forecast performance sensitivity	0.0364	2.66***
λ₃ tau persistence Long-term factor persistence	0.9616	66.37***

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ThyssenKrupp AG MF2-GARCH Volatility Analysis

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News Impact Curve

Volatility Forecast

Parameter Estimates

Other ThyssenKrupp AG Analyses