Deutsche Bank FX 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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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	91
αARCH	0.1644	6.26***
βGARCH	0.8227	48.68***
γleverage	-0.0964	-4.01***
λ₁tau intercept	0.0002	1.70*
λ₂forecast adj.	0.9793	15.85***
λ₃tau persistence	0.0207	0.68

Parameter	Value	t-statistic
m window Rolling window length	91
α ARCH Response to squared shocks	0.1644	6.26***
β GARCH Volatility persistence	0.8227	48.68***
γ leverage Additional response to negative shocks	-0.0964	-4.01***
λ₁ tau intercept Baseline long-term coefficient	0.0002	1.70*
λ₂ forecast adj. Forecast performance sensitivity	0.9793	15.85***
λ₃ tau persistence Long-term factor persistence	0.0207	0.68

V-Lab

US Dollar to Indian Rupee MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other US Dollar to Indian Rupee Analyses