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	1.6839	1.64
αARCH	0.0992	5.25***
βGARCH	0.8279	19.36***

γ₁	1.4992	2.93***
γ₂	-1.6715	-2.04**
γ₃	-0.5004	-0.75
γ₄	1.4890	2.61***
γ₅	-2.2589	-3.67***
γ₆	2.7521	3.87***
γ₇	-1.7323	-2.48**
γ₈	0.0472	0.05

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.6839	1.64
α ARCH Response to squared shocks	0.0992	5.25***
β GARCH Volatility persistence	0.8279	19.36***

γ₁	1.4992	2.93***
γ₂	-1.6715	-2.04**
γ₃	-0.5004	-0.75
γ₄	1.4890	2.61***
γ₅	-2.2589	-3.67***
γ₆	2.7521	3.87***
γ₇	-1.7323	-2.48**
γ₈	0.0472	0.05

V-Lab

Suez Canal Co for Technology Settling Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Suez Canal Co for Technology Settling Analyses