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	1.3471	5.61***
αARCH	0.2897	5.11***
βGARCH	0.1848	2.12**

γ₁	0.1940	2.01**
γ₂	-0.2058	-1.39
γ₃	-0.0804	-0.71
γ₄	0.1731	1.82*
γ₅	-0.1441	-1.93*
γ₆	0.1011	2.08**

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3471	5.61***
α ARCH Response to squared shocks	0.2897	5.11***
β GARCH Volatility persistence	0.1848	2.12**

γ₁	0.1940	2.01**
γ₂	-0.2058	-1.39
γ₃	-0.0804	-0.71
γ₄	0.1731	1.82*
γ₅	-0.1441	-1.93*
γ₆	0.1011	2.08**

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