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	1.5846	1.57
αARCH	0.0883	4.89***
βGARCH	0.8381	19.26***

γ₁	1.4409	2.65***
γ₂	-1.5653	-1.84*
γ₃	-0.6035	-0.91
γ₄	1.5967	2.84***
γ₅	-2.3433	-3.95***
γ₆	2.7376	4.02***
γ₇	-1.5253	-2.24**
γ₈	-0.4741	-0.57

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.5846	1.57
α ARCH Response to squared shocks	0.0883	4.89***
β GARCH Volatility persistence	0.8381	19.26***

γ₁	1.4409	2.65***
γ₂	-1.5653	-1.84*
γ₃	-0.6035	-0.91
γ₄	1.5967	2.84***
γ₅	-2.3433	-3.95***
γ₆	2.7376	4.02***
γ₇	-1.5253	-2.24**
γ₈	-0.4741	-0.57

V-Lab

Suez Canal Co for Technology Settling Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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