CBOE IBM Volatility Index

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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
ωconst	0.0240	4.18***
αARCH	0.0663	7.73***
βGARCH	0.9334	110.00***
γleverage	0.4518	3.87***
δpower	0.5567	4.52***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.0240	4.18***
α ARCH Response to squared shocks	0.0663	7.73***
β GARCH Volatility persistence	0.9334	110.00***
γ leverage Additional response to negative shocks	0.4518	3.87***
δ power Transformation power	0.5567	4.52***

V-Lab

International Business Machines Corp APARCH Volatility Analysis

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News Impact Curve

Volatility Forecast

Parameter Estimates

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