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	2.8936	1.84*
αARCH	0.4362	3.39***
βGARCH	0.3747	4.18***

γ₁	0.9482	0.81
γ₂	-1.2386	-0.69
γ₃	0.3649	0.31
γ₄	-0.4368	-0.47
γ₅	2.1528	2.65***
γ₆	-4.6677	-6.42***
γ₇	5.1619	7.16***
γ₈	-3.7361	-3.73***
γ₉	2.2021	2.46**
γ₁₀	-0.8163	-1.66*

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.8936	1.84*
α ARCH Response to squared shocks	0.4362	3.39***
β GARCH Volatility persistence	0.3747	4.18***

γ₁	0.9482	0.81
γ₂	-1.2386	-0.69
γ₃	0.3649	0.31
γ₄	-0.4368	-0.47
γ₅	2.1528	2.65***
γ₆	-4.6677	-6.42***
γ₇	5.1619	7.16***
γ₈	-3.7361	-3.73***
γ₉	2.2021	2.46**
γ₁₀	-0.8163	-1.66*

V-Lab

Premier Fund Reit Zero Slope Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Premier Fund Reit Analyses