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	1.0591	3.01***
αARCH	0.0919	3.87***
βGARCH	0.9073	38.81***

γ₁	-0.0728	-0.01
γ₂	0.2422	0.02
γ₃	1.5105	0.29
γ₄	-6.9676	-1.81*
γ₅	15.8185	3.14***
γ₆	-23.3063	-3.69***
γ₇	19.9260	3.32***
γ₈	-3.5210	-0.28

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0591	3.01***
α ARCH Response to squared shocks	0.0919	3.87***
β GARCH Volatility persistence	0.9073	38.81***

γ₁	-0.0728	-0.01
γ₂	0.2422	0.02
γ₃	1.5105	0.29
γ₄	-6.9676	-1.81*
γ₅	15.8185	3.14***
γ₆	-23.3063	-3.69***
γ₇	19.9260	3.32***
γ₈	-3.5210	-0.28

V-Lab

ECP Emerging Growth Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other ECP Emerging Growth Ltd Analyses