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
ωconst	0.9638	6.33***
αARCH	0.1139	10.13***
βGARCH	0.8807	75.80***

γ₁	-0.0796	-8.46***
γ₂	0.1752	8.35***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.9638	6.33***
α ARCH Response to squared shocks	0.1139	10.13***
β GARCH Volatility persistence	0.8807	75.80***

γ₁	-0.0796	-8.46***
γ₂	0.1752	8.35***

V-Lab

Log-In Logistica Intermodal Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Log-In Logistica Intermodal Analyses