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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	36
αARCH	0.3127	5.10***
βGARCH	0.2434	4.09***
γleverage	0.0362	0.27
λ₁tau intercept	5.5521	1.17
λ₂forecast adj.	0.2550	1.69*
λ₃tau persistence	0.6697	3.15***

Parameter	Value	t-statistic
m window Rolling window length	36
α ARCH Response to squared shocks	0.3127	5.10***
β GARCH Volatility persistence	0.2434	4.09***
γ leverage Additional response to negative shocks	0.0362	0.27
λ₁ tau intercept Baseline long-term coefficient	5.5521	1.17
λ₂ forecast adj. Forecast performance sensitivity	0.2550	1.69*
λ₃ tau persistence Long-term factor persistence	0.6697	3.15***

V-Lab

Smart Powerr Corp MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

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