CBOE Volatility Index

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How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

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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	101
αARCH	0.0000	0.00
βGARCH	0.9043	38.08***
γleverage	0.0852	4.28***
λ₁tau intercept	0.5053	0.43
λ₂forecast adj.	0.3643	0.47
λ₃tau persistence	0.3073	0.20

Parameter	Value	t-statistic
m window Rolling window length	101
α ARCH Response to squared shocks	0.0000	0.00
β GARCH Volatility persistence	0.9043	38.08***
γ leverage Additional response to negative shocks	0.0852	4.28***
λ₁ tau intercept Baseline long-term coefficient	0.5053	0.43
λ₂ forecast adj. Forecast performance sensitivity	0.3643	0.47
λ₃ tau persistence Long-term factor persistence	0.3073	0.20

V-Lab

First Trust India Nifty 50 Equ MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other First Trust India Nifty 50 Equ Analyses