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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	61
αARCH	0.0209	1.98**
βGARCH	0.9095	41.14***
γleverage	0.0585	3.89***
λ₁tau intercept	0.0052	0.47
λ₂forecast adj.	0.0029	0.77
λ₃tau persistence	0.9956	150.67***

Parameter	Value	t-statistic
m window Rolling window length	61
α ARCH Response to squared shocks	0.0209	1.98**
β GARCH Volatility persistence	0.9095	41.14***
γ leverage Additional response to negative shocks	0.0585	3.89***
λ₁ tau intercept Baseline long-term coefficient	0.0052	0.47
λ₂ forecast adj. Forecast performance sensitivity	0.0029	0.77
λ₃ tau persistence Long-term factor persistence	0.9956	150.67***

V-Lab

Alphabet Inc MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Alphabet Inc Analyses