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	21
αARCH	0.0379	2.30**
βGARCH	0.7873	37.28***
γleverage	0.1424	7.27***
λ₁tau intercept	0.0047	1.92*
λ₂forecast adj.	0.0477	4.89***
λ₃tau persistence	0.9509	100.68***

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.0379	2.30**
β GARCH Volatility persistence	0.7873	37.28***
γ leverage Additional response to negative shocks	0.1424	7.27***
λ₁ tau intercept Baseline long-term coefficient	0.0047	1.92*
λ₂ forecast adj. Forecast performance sensitivity	0.0477	4.89***
λ₃ tau persistence Long-term factor persistence	0.9509	100.68***

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S&P BSE SENSEX Index MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other S&P BSE SENSEX Index Analyses