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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
mwindow	41
αARCH	0.0000	0.00
βGARCH	0.9098	40.50***
γleverage	0.1311	3.58***
λ₁tau intercept	10.0000	1.48
λ₂forecast adj.	0.8166	5.12***
λ₃tau persistence	0.0000	0.00

Parameter	Value	t-statistic
m window Rolling window length	41
α ARCH Response to squared shocks	0.0000	0.00
β GARCH Volatility persistence	0.9098	40.50***
γ leverage Additional response to negative shocks	0.1311	3.58***
λ₁ tau intercept Baseline long-term coefficient	10.0000	1.48
λ₂ forecast adj. Forecast performance sensitivity	0.8166	5.12***
λ₃ tau persistence Long-term factor persistence	0.0000	0.00

V-Lab

Global Mofy AI Ltd MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

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