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
mwindow	126
αARCH	0.1410	5.06***
βGARCH	0.8084	26.15***
γleverage	-0.1174	-3.61***
λ₁tau intercept	0.0344	0.40
λ₂forecast adj.	0.0000	0.01
λ₃tau persistence	0.9987	225.29***

Parameter	Value	t-statistic
m window Rolling window length	126
α ARCH Response to squared shocks	0.1410	5.06***
β GARCH Volatility persistence	0.8084	26.15***
γ leverage Additional response to negative shocks	-0.1174	-3.61***
λ₁ tau intercept Baseline long-term coefficient	0.0344	0.40
λ₂ forecast adj. Forecast performance sensitivity	0.0000	0.01
λ₃ tau persistence Long-term factor persistence	0.9987	225.29***

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India NSE Volatility Index MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

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