CBOE Volatility Index

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CBOE DJIA 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	1.0900	7.46***
αARCH	0.0850	8.35***
βGARCH	0.8381	45.47***

γ₁	0.0035	0.12
γ₂	0.0442	1.04
γ₃	-0.1632	-5.18***
γ₄	0.2155	7.16***
γ₅	-0.1479	-4.54***
γ₆	0.0674	1.91*
γ₇	-0.0058	-0.18
γ₈	-0.0324	-1.02
γ₉	0.0420	0.92

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0900	7.46***
α ARCH Response to squared shocks	0.0850	8.35***
β GARCH Volatility persistence	0.8381	45.47***

γ₁	0.0035	0.12
γ₂	0.0442	1.04
γ₃	-0.1632	-5.18***
γ₄	0.2155	7.16***
γ₅	-0.1479	-4.54***
γ₆	0.0674	1.91*
γ₇	-0.0058	-0.18
γ₈	-0.0324	-1.02
γ₉	0.0420	0.92

V-Lab

Procter & Gamble Co/The Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Procter & Gamble Co/The Analyses