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
mwindow	66
αARCH	0.5070	4.09***
βGARCH	0.4218	5.57***
γleverage	-0.5000	-4.02***
λ₁tau intercept	0.0605	0.33
λ₂forecast adj.	0.0099	1.52
λ₃tau persistence	0.9891	145.91***

Parameter	Value	t-statistic
m window Rolling window length	66
α ARCH Response to squared shocks	0.5070	4.09***
β GARCH Volatility persistence	0.4218	5.57***
γ leverage Additional response to negative shocks	-0.5000	-4.02***
λ₁ tau intercept Baseline long-term coefficient	0.0605	0.33
λ₂ forecast adj. Forecast performance sensitivity	0.0099	1.52
λ₃ tau persistence Long-term factor persistence	0.9891	145.91***

V-Lab

CBOE Amazon Volatility Index MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other CBOE Amazon Volatility Index Analyses