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	1.5151	3.11***
αARCH	0.0893	5.08***
βGARCH	0.7561	18.14***

γ₁	0.0178	0.17
γ₂	0.0191	0.14
γ₃	0.0249	0.43
γ₄	-0.2495	-5.16***
γ₅	0.3842	8.68***
γ₆	-0.3203	-6.97***
γ₇	0.1797	3.94***
γ₈	-0.0692	-1.79*
γ₉	0.0162	0.63

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.5151	3.11***
α ARCH Response to squared shocks	0.0893	5.08***
β GARCH Volatility persistence	0.7561	18.14***

γ₁	0.0178	0.17
γ₂	0.0191	0.14
γ₃	0.0249	0.43
γ₄	-0.2495	-5.16***
γ₅	0.3842	8.68***
γ₆	-0.3203	-6.97***
γ₇	0.1797	3.94***
γ₈	-0.0692	-1.79*
γ₉	0.0162	0.63

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