India NSE Volatility Index

CBOE Emerging Market Markets Volatility Index

How volatility evolves over time

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{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	1.9372	2.39**
αARCH	0.2160	5.18***
βGARCH	0.4608	5.02***

γ₁	-0.4108	-0.15
γ₂	1.9092	0.45
γ₃	-3.6227	-1.11
γ₄	4.9579	2.03**
γ₅	-6.4973	-3.32***
γ₆	6.8744	3.03***
γ₇	-5.4497	-1.58
γ₈	5.0812	1.38
γ₉	-5.4648	-2.37**
γ₁₀	3.5962	3.22***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.9372	2.39**
α ARCH Response to squared shocks	0.2160	5.18***
β GARCH Volatility persistence	0.4608	5.02***

γ₁	-0.4108	-0.15
γ₂	1.9092	0.45
γ₃	-3.6227	-1.11
γ₄	4.9579	2.03**
γ₅	-6.4973	-3.32***
γ₆	6.8744	3.03***
γ₇	-5.4497	-1.58
γ₈	5.0812	1.38
γ₉	-5.4648	-2.37**
γ₁₀	3.5962	3.22***

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