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	51
αARCH	0.1530	5.11***
βGARCH	0.7932	23.17***
γleverage	-0.1319	-3.94***
λ₁tau intercept	0.1107	0.90
λ₂forecast adj.	0.0025	1.01
λ₃tau persistence	0.9935	163.52***

Parameter	Value	t-statistic
m window Rolling window length	51
α ARCH Response to squared shocks	0.1530	5.11***
β GARCH Volatility persistence	0.7932	23.17***
γ leverage Additional response to negative shocks	-0.1319	-3.94***
λ₁ tau intercept Baseline long-term coefficient	0.1107	0.90
λ₂ forecast adj. Forecast performance sensitivity	0.0025	1.01
λ₃ tau persistence Long-term factor persistence	0.9935	163.52***

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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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