India NSE Volatility Index

CBOE Emerging Market Markets Volatility Index

How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

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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
ωconst	1.7461	1.93*
αARCH	0.3348	5.47***
βGARCH	0.6357	9.80***

γ₁	-2.9831	-0.17
γ₂	20.9427	0.57
γ₃	-85.0209	-1.43
γ₄	164.8173	1.96**
γ₅	-154.4892	-2.33**
γ₆	76.5725	3.14***
γ₇	-33.5468	-3.52***
γ₈	15.1981	0.97
γ₉	9.9878	0.40

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.7461	1.93*
α ARCH Response to squared shocks	0.3348	5.47***
β GARCH Volatility persistence	0.6357	9.80***

γ₁	-2.9831	-0.17
γ₂	20.9427	0.57
γ₃	-85.0209	-1.43
γ₄	164.8173	1.96**
γ₅	-154.4892	-2.33**
γ₆	76.5725	3.14***
γ₇	-33.5468	-3.52***
γ₈	15.1981	0.97
γ₉	9.9878	0.40

V-Lab

RGF Capital Markets Ltd Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other RGF Capital Markets Ltd Analyses