CBOE Volatility Index

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CBOE DJIA Volatility Index

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How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

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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	1.0000	1.66*
αARCH	0.1798	4.41***
βGARCH	0.4979	3.62***
γleverage	-0.0137	-0.07
δpower	0.5000	2.16**

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0000	1.66*
α ARCH Response to squared shocks	0.1798	4.41***
β GARCH Volatility persistence	0.4979	3.62***
γ leverage Additional response to negative shocks	-0.0137	-0.07
δ power Transformation power	0.5000	2.16**

V-Lab

CBOE Google Volatility Index APARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other CBOE Google Volatility Index Analyses