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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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
mwindow	126
αARCH	0.4714	4.60***
βGARCH	0.3908	4.47***
γleverage	-0.4489	-4.42***
λ₁tau intercept	10.0000	0.13
λ₂forecast adj.	0.0000	0.00
λ₃tau persistence	0.8366	0.62

Parameter	Value	t-statistic
m window Rolling window length	126
α ARCH Response to squared shocks	0.4714	4.60***
β GARCH Volatility persistence	0.3908	4.47***
γ leverage Additional response to negative shocks	-0.4489	-4.42***
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.13
λ₂ forecast adj. Forecast performance sensitivity	0.0000	0.00
λ₃ tau persistence Long-term factor persistence	0.8366	0.62

V-Lab

CBOE IBM Volatility Index MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other CBOE IBM Volatility Index Analyses