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	21
αARCH	0.2425	4.69***
βGARCH	0.6120	8.31***
γleverage	-0.2243	-3.98***
λ₁tau intercept	4.8452	1.03
λ₂forecast adj.	0.1791	0.98
λ₃tau persistence	0.4146	0.73

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.2425	4.69***
β GARCH Volatility persistence	0.6120	8.31***
γ leverage Additional response to negative shocks	-0.2243	-3.98***
λ₁ tau intercept Baseline long-term coefficient	4.8452	1.03
λ₂ forecast adj. Forecast performance sensitivity	0.1791	0.98
λ₃ tau persistence Long-term factor persistence	0.4146	0.73

V-Lab

Direxion Daily AI and Big Data Bear 2X ETF MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Direxion Daily AI and Big Data Bear 2X ETF Analyses