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	0.0137	4.65***
αARCH	0.0882	7.82***
βGARCH	0.9110	111.25***
γleverage	0.1382	3.06***
δpower	1.9727	8.52***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.0137	4.65***
α ARCH Response to squared shocks	0.0882	7.82***
β GARCH Volatility persistence	0.9110	111.25***
γ leverage Additional response to negative shocks	0.1382	3.06***
δ power Transformation power	1.9727	8.52***

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