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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	41
αARCH	0.0668	4.10***
βGARCH	0.0000	0.00
γleverage	0.0008	0.03
λ₁tau intercept	0.0042	2.65***
λ₂forecast adj.	0.1409	3.45***
λ₃tau persistence	0.8413	18.39***

Parameter	Value	t-statistic
m window Rolling window length	41
α ARCH Response to squared shocks	0.0668	4.10***
β GARCH Volatility persistence	0.0000	0.00
γ leverage Additional response to negative shocks	0.0008	0.03
λ₁ tau intercept Baseline long-term coefficient	0.0042	2.65***
λ₂ forecast adj. Forecast performance sensitivity	0.1409	3.45***
λ₃ tau persistence Long-term factor persistence	0.8413	18.39***

V-Lab

US Dollar to Euro MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other US Dollar to Euro Analyses