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	5.7953	3.29***
αARCH	0.4567	8.43***
βGARCH	0.5357	10.20***

γ₁	0.6625	0.67
γ₂	-0.9154	-0.58
γ₃	1.8504	1.22
γ₄	-4.5032	-2.35**
γ₅	6.3842	3.16***
γ₆	-23.2695	-3.04***
γ₇	53.7673	2.88***
γ₈	-50.9241	-2.86***
γ₉	18.1113	2.89***

Parameter	Value	t-statistic
ω const Unconditional variance weight	5.7953	3.29***
α ARCH Response to squared shocks	0.4567	8.43***
β GARCH Volatility persistence	0.5357	10.20***

γ₁	0.6625	0.67
γ₂	-0.9154	-0.58
γ₃	1.8504	1.22
γ₄	-4.5032	-2.35**
γ₅	6.3842	3.16***
γ₆	-23.2695	-3.04***
γ₇	53.7673	2.88***
γ₈	-50.9241	-2.86***
γ₉	18.1113	2.89***

V-Lab

Chitec Technology Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Chitec Technology Corp Analyses