How volatility evolves over time

How illiquidity evolves over time

{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
mwindow	106
αARCH	0.3295	3.15***
βGARCH	0.8275	26.96***
γleverage	-0.3295	-2.43**
λ₁tau intercept	0.0000	0.11
λ₂forecast adj.	0.0016	0.66
λ₃tau persistence	0.8505	29.29***

Parameter	Value	t-statistic
m window Rolling window length	106
α ARCH Response to squared shocks	0.3295	3.15***
β GARCH Volatility persistence	0.8275	26.96***
γ leverage Additional response to negative shocks	-0.3295	-2.43**
λ₁ tau intercept Baseline long-term coefficient	0.0000	0.11
λ₂ forecast adj. Forecast performance sensitivity	0.0016	0.66
λ₃ tau persistence Long-term factor persistence	0.8505	29.29***

V-Lab

Grimoldi SA ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Grimoldi SA Analyses