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	36
αARCH	0.1913	7.12***
βGARCH	0.7246	26.30***
γleverage	-0.1913	-4.88***
λ₁tau intercept	9.2366	1.01
λ₂forecast adj.	0.0917	2.97***
λ₃tau persistence	0.9078	29.78***

Parameter	Value	t-statistic
m window Rolling window length	36
α ARCH Response to squared shocks	0.1913	7.12***
β GARCH Volatility persistence	0.7246	26.30***
γ leverage Additional response to negative shocks	-0.1913	-4.88***
λ₁ tau intercept Baseline long-term coefficient	9.2366	1.01
λ₂ forecast adj. Forecast performance sensitivity	0.0917	2.97***
λ₃ tau persistence Long-term factor persistence	0.9078	29.78***

V-Lab

Sixt SE ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Sixt SE Analyses