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

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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	0.2705	1.05
αARCH	0.0741	1.23
βGARCH	0.6287	2.00**
γleverage	1.0000	21.47***
δpower	0.6635	0.72

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.2705	1.05
α ARCH Response to squared shocks	0.0741	1.23
β GARCH Volatility persistence	0.6287	2.00**
γ leverage Additional response to negative shocks	1.0000	21.47***
δ power Transformation power	0.6635	0.72

V-Lab

Calamos Autocallable INM ETF APARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Calamos Autocallable INM ETF Analyses