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How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

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
ωconst	0.4184	2.88***
αARCH	0.0654	2.56**
βGARCH	0.8508	29.15***
γleverage	0.1032	1.56

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.4184	2.88***
α ARCH Response to squared shocks	0.0654	2.56**
β GARCH Volatility persistence	0.8508	29.15***
γ leverage Additional response to negative shocks	0.1032	1.56

V-Lab

Landi Renzo SPA GJR-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Landi Renzo SPA Analyses