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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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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	36
αARCH	0.0640	2.48**
βGARCH	0.7081	14.82***
γleverage	0.1080	2.41**
λ₁tau intercept	0.0495	1.03
λ₂forecast adj.	0.0136	1.88*
λ₃tau persistence	0.9834	107.73***

Parameter	Value	t-statistic
m window Rolling window length	36
α ARCH Response to squared shocks	0.0640	2.48**
β GARCH Volatility persistence	0.7081	14.82***
γ leverage Additional response to negative shocks	0.1080	2.41**
λ₁ tau intercept Baseline long-term coefficient	0.0495	1.03
λ₂ forecast adj. Forecast performance sensitivity	0.0136	1.88*
λ₃ tau persistence Long-term factor persistence	0.9834	107.73***

V-Lab

Ethereum to US Dollar MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Ethereum to US Dollar Analyses