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	4.3847	1.72*
αARCH	0.0452	1.92*
βGARCH	0.8984	63.94***
γleverage	0.1014	2.13**

Parameter	Value	t-statistic
ω const Unconditional variance weight	4.3847	1.72*
α ARCH Response to squared shocks	0.0452	1.92*
β GARCH Volatility persistence	0.8984	63.94***
γ leverage Additional response to negative shocks	0.1014	2.13**

V-Lab

Hoegh Autoliners Asa Asymmetric ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Hoegh Autoliners Asa Analyses