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	5.0000	0.45
αARCH	0.0597	5.26***
βGARCH	0.9133	108.78***
γleverage	0.0540	3.20***

Parameter	Value	t-statistic
ω const Unconditional variance weight	5.0000	0.45
α ARCH Response to squared shocks	0.0597	5.26***
β GARCH Volatility persistence	0.9133	108.78***
γ leverage Additional response to negative shocks	0.0540	3.20***

V-Lab

Log-In Logistica Intermodal Asymmetric ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Log-In Logistica Intermodal Analyses