India NSE Volatility Index

CBOE Emerging Market Markets 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	0.1218	0.09
αARCH	0.3191	0.05
βGARCH	0.6809	0.11

γ₁	-7.9271	-0.01
γ₂	32.3821	0.01
γ₃	-73.9280	-0.03
γ₄	127.3171	0.09
γ₅	-165.1821	-0.46
γ₆	158.9706	0.30
γ₇	-114.9673	-0.04
γ₈	67.4578	0.01
γ₉	-35.7022	-0.01

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.1218	0.09
α ARCH Response to squared shocks	0.3191	0.05
β GARCH Volatility persistence	0.6809	0.11

γ₁	-7.9271	-0.01
γ₂	32.3821	0.01
γ₃	-73.9280	-0.03
γ₄	127.3171	0.09
γ₅	-165.1821	-0.46
γ₆	158.9706	0.30
γ₇	-114.9673	-0.04
γ₈	67.4578	0.01
γ₉	-35.7022	-0.01

V-Lab

Ashika Global Securities Ltd Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Ashika Global Securities Ltd Analyses