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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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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
ωconst	0.0607	0.83
αARCH	0.1754	1.50
βGARCH	0.9939	78.16***
γleverage	-0.0049	-0.08

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.0607	0.83
α ARCH Response to squared shocks	0.1754	1.50
β GARCH Volatility persistence	0.9939	78.16***
γ leverage Additional response to negative shocks	-0.0049	-0.08

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Global Mofy AI Ltd EGARCH Volatility Analysis

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News Impact Curve

Volatility Forecast

Parameter Estimates

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