CBOE 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

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	1.3450	5.62***
αARCH	0.2899	5.12***
βGARCH	0.1815	2.11**

γ₁	0.1949	2.00**
γ₂	-0.2065	-1.38
γ₃	-0.0799	-0.70
γ₄	0.1689	1.76*
γ₅	-0.1342	-1.78*
γ₆	0.0909	1.84*

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3450	5.62***
α ARCH Response to squared shocks	0.2899	5.12***
β GARCH Volatility persistence	0.1815	2.11**

γ₁	0.1949	2.00**
γ₂	-0.2065	-1.38
γ₃	-0.0799	-0.70
γ₄	0.1689	1.76*
γ₅	-0.1342	-1.78*
γ₆	0.0909	1.84*

V-Lab

CBOE Google Volatility Index Zero Slope Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other CBOE Google Volatility Index Analyses