CBOE Volatility Index

How volatility evolves over time

How illiquidity evolves over time

{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	1.0473	8.83***
αARCH	0.1738	8.10***
βGARCH	0.6257	13.52***

γ₁	0.1322	2.22**
γ₂	-0.2238	-2.47**
γ₃	0.2027	3.17***
γ₄	-0.2564	-4.14***
γ₅	0.1497	2.34**
γ₆	0.0620	1.23

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0473	8.83***
α ARCH Response to squared shocks	0.1738	8.10***
β GARCH Volatility persistence	0.6257	13.52***

γ₁	0.1322	2.22**
γ₂	-0.2238	-2.47**
γ₃	0.2027	3.17***
γ₄	-0.2564	-4.14***
γ₅	0.1497	2.34**
γ₆	0.0620	1.23

V-Lab

Vinalink Intl Freight Forwar Zero Slope Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Vinalink Intl Freight Forwar Analyses