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	5.7323	3.29***
αARCH	0.4520	8.58***
βGARCH	0.5403	10.60***

γ₁	0.7000	0.70
γ₂	-0.9961	-0.62
γ₃	1.9527	1.27
γ₄	-4.6227	-2.39**
γ₅	6.4860	3.21***
γ₆	-22.8099	-3.12***
γ₇	52.0885	2.96***
γ₈	-48.8414	-2.92***
γ₉	16.5531	2.78***

Parameter	Value	t-statistic
ω const Unconditional variance weight	5.7323	3.29***
α ARCH Response to squared shocks	0.4520	8.58***
β GARCH Volatility persistence	0.5403	10.60***

γ₁	0.7000	0.70
γ₂	-0.9961	-0.62
γ₃	1.9527	1.27
γ₄	-4.6227	-2.39**
γ₅	6.4860	3.21***
γ₆	-22.8099	-3.12***
γ₇	52.0885	2.96***
γ₈	-48.8414	-2.92***
γ₉	16.5531	2.78***

V-Lab

Chitec Technology Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Chitec Technology Corp Analyses