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	5.8540	3.29***
αARCH	0.4626	8.19***
βGARCH	0.5299	9.64***

γ₁	0.5930	0.62
γ₂	-0.7664	-0.50
γ₃	1.6573	1.11
γ₄	-4.2688	-2.27**
γ₅	6.1776	3.08***
γ₆	-23.7719	-2.86***
γ₇	55.7828	2.69***
γ₈	-53.4551	-2.69***
γ₉	19.9441	2.91***

Parameter	Value	t-statistic
ω const Unconditional variance weight	5.8540	3.29***
α ARCH Response to squared shocks	0.4626	8.19***
β GARCH Volatility persistence	0.5299	9.64***

γ₁	0.5930	0.62
γ₂	-0.7664	-0.50
γ₃	1.6573	1.11
γ₄	-4.2688	-2.27**
γ₅	6.1776	3.08***
γ₆	-23.7719	-2.86***
γ₇	55.7828	2.69***
γ₈	-53.4551	-2.69***
γ₉	19.9441	2.91***

V-Lab

Chitec Technology Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Chitec Technology Corp Analyses