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

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	1.5140	3.10***
αARCH	0.0898	5.10***
βGARCH	0.7551	18.11***

γ₁	0.0181	0.17
γ₂	0.0180	0.13
γ₃	0.0273	0.47
γ₄	-0.2528	-5.22***
γ₅	0.3866	8.70***
γ₆	-0.3207	-6.93***
γ₇	0.1791	3.91***
γ₈	-0.0687	-1.77*
γ₉	0.0161	0.62

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.5140	3.10***
α ARCH Response to squared shocks	0.0898	5.10***
β GARCH Volatility persistence	0.7551	18.11***

γ₁	0.0181	0.17
γ₂	0.0180	0.13
γ₃	0.0273	0.47
γ₄	-0.2528	-5.22***
γ₅	0.3866	8.70***
γ₆	-0.3207	-6.93***
γ₇	0.1791	3.91***
γ₈	-0.0687	-1.77*
γ₉	0.0161	0.62

V-Lab

ICE US Sugar Zero Slope Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other ICE US Sugar Analyses