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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	66
αARCH	0.0630	4.02***
βGARCH	0.7930	32.17***
γleverage	0.0406	2.04**
λ₁tau intercept	0.1266	1.58
λ₂forecast adj.	0.2552	2.05**
λ₃tau persistence	0.6991	4.74***

Parameter	Value	t-statistic
m window Rolling window length	66
α ARCH Response to squared shocks	0.0630	4.02***
β GARCH Volatility persistence	0.7930	32.17***
γ leverage Additional response to negative shocks	0.0406	2.04**
λ₁ tau intercept Baseline long-term coefficient	0.1266	1.58
λ₂ forecast adj. Forecast performance sensitivity	0.2552	2.05**
λ₃ tau persistence Long-term factor persistence	0.6991	4.74***

V-Lab

Deutsche Telekom AG MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Deutsche Telekom AG Analyses