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	5.6448	3.29***
αARCH	0.4443	8.89***
βGARCH	0.5479	11.41***

γ₁	0.7766	0.76
γ₂	-1.1593	-0.71
γ₃	2.1590	1.37
γ₄	-4.8612	-2.48**
γ₅	6.6840	3.31***
γ₆	-21.7526	-3.30***
γ₇	48.4010	3.14***
γ₈	-44.5973	-3.07***
γ₉	14.2642	2.77***

Parameter	Value	t-statistic
ω const Unconditional variance weight	5.6448	3.29***
α ARCH Response to squared shocks	0.4443	8.89***
β GARCH Volatility persistence	0.5479	11.41***

γ₁	0.7766	0.76
γ₂	-1.1593	-0.71
γ₃	2.1590	1.37
γ₄	-4.8612	-2.48**
γ₅	6.6840	3.31***
γ₆	-21.7526	-3.30***
γ₇	48.4010	3.14***
γ₈	-44.5973	-3.07***
γ₉	14.2642	2.77***

V-Lab

Chitec Technology Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Chitec Technology Corp Analyses