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	1.8185	3.77***
αARCH	0.1423	5.20***
βGARCH	0.6367	8.93***

γ₁	0.0844	0.71
γ₂	-0.1068	-0.68
γ₃	0.1867	1.67*
γ₄	-0.3937	-2.99***
γ₅	0.3636	2.87***
γ₆	-0.1570	-1.49
γ₇	0.0038	0.04
γ₈	0.0531	0.64
γ₉	-0.0475	-0.81

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.8185	3.77***
α ARCH Response to squared shocks	0.1423	5.20***
β GARCH Volatility persistence	0.6367	8.93***

γ₁	0.0844	0.71
γ₂	-0.1068	-0.68
γ₃	0.1867	1.67*
γ₄	-0.3937	-2.99***
γ₅	0.3636	2.87***
γ₆	-0.1570	-1.49
γ₇	0.0038	0.04
γ₈	0.0531	0.64
γ₉	-0.0475	-0.81

V-Lab

Kei Industries Ltd Zero Slope Spline-GARCH Volatility Analysis

Date Range:

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