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	46
αARCH	0.1364	7.57***
βGARCH	0.6809	35.05***
γleverage	0.3650	10.90***
λ₁tau intercept	0.1941	0.00
λ₂forecast adj.	0.0445	1.51
λ₃tau persistence	0.9555	35.79***

Parameter	Value	t-statistic
m window Rolling window length	46
α ARCH Response to squared shocks	0.1364	7.57***
β GARCH Volatility persistence	0.6809	35.05***
γ leverage Additional response to negative shocks	0.3650	10.90***
λ₁ tau intercept Baseline long-term coefficient	0.1941	0.00
λ₂ forecast adj. Forecast performance sensitivity	0.0445	1.51
λ₃ tau persistence Long-term factor persistence	0.9555	35.79***

V-Lab

Vitura SA ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Vitura SA Analyses