India NSE Volatility Index

CBOE Emerging Market Markets Volatility Index

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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	1.6657	1.74*
αARCH	0.3345	5.39***
βGARCH	0.6402	9.93***

γ₁	-5.4280	-0.29
γ₂	24.1846	0.63
γ₃	-84.5843	-1.40
γ₄	160.6831	1.89*
γ₅	-150.0843	-2.23**
γ₆	75.3951	3.05***
γ₇	-35.5023	-4.11***
γ₈	21.3890	1.87*
γ₉	-5.8885	-0.56

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.6657	1.74*
α ARCH Response to squared shocks	0.3345	5.39***
β GARCH Volatility persistence	0.6402	9.93***

γ₁	-5.4280	-0.29
γ₂	24.1846	0.63
γ₃	-84.5843	-1.40
γ₄	160.6831	1.89*
γ₅	-150.0843	-2.23**
γ₆	75.3951	3.05***
γ₇	-35.5023	-4.11***
γ₈	21.3890	1.87*
γ₉	-5.8885	-0.56

V-Lab

RGF Capital Markets Ltd Zero Slope Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

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