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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	66
αARCH	0.1083	3.17***
βGARCH	0.5625	9.10***
γleverage	0.0198	0.57
λ₁tau intercept	0.5513	1.43
λ₂forecast adj.	0.3322	1.58
λ₃tau persistence	0.5810	2.16**

Parameter	Value	t-statistic
m window Rolling window length	66
α ARCH Response to squared shocks	0.1083	3.17***
β GARCH Volatility persistence	0.5625	9.10***
γ leverage Additional response to negative shocks	0.0198	0.57
λ₁ tau intercept Baseline long-term coefficient	0.5513	1.43
λ₂ forecast adj. Forecast performance sensitivity	0.3322	1.58
λ₃ tau persistence Long-term factor persistence	0.5810	2.16**

V-Lab

Kelly Services Inc MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Kelly Services Inc Analyses