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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	2.0592	2.87***
αARCH	0.3571	3.82***
βGARCH	0.7619	21.12***
γleverage	0.1033	0.06

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.0592	2.87***
α ARCH Response to squared shocks	0.3571	3.82***
β GARCH Volatility persistence	0.7619	21.12***
γ leverage Additional response to negative shocks	0.1033	0.06

V-Lab

MindForge Inc AGARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other MindForge Inc Analyses