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	1.1410	5.33***
αARCH	0.0907	8.92***
βGARCH	0.8790	72.08***

γ₁	-0.1363	-2.80***
γ₂	0.2588	3.58***
γ₃	-0.2518	-5.17***
γ₄	0.2480	5.17***
γ₅	-0.2002	-4.43***
γ₆	0.1007	2.50**
γ₇	0.0053	0.13
γ₈	-0.0487	-1.11
γ₉	0.0371	1.15

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1410	5.33***
α ARCH Response to squared shocks	0.0907	8.92***
β GARCH Volatility persistence	0.8790	72.08***

γ₁	-0.1363	-2.80***
γ₂	0.2588	3.58***
γ₃	-0.2518	-5.17***
γ₄	0.2480	5.17***
γ₅	-0.2002	-4.43***
γ₆	0.1007	2.50**
γ₇	0.0053	0.13
γ₈	-0.0487	-1.11
γ₉	0.0371	1.15

V-Lab

S&P BSE SENSEX Index Zero Slope Spline-GARCH Volatility Analysis

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