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	2.3726	5.22***
αARCH	0.1108	6.31***
βGARCH	0.8866	54.77***

γ₁	-0.7486	-4.51***
γ₂	1.3681	4.66***
γ₃	-0.7264	-3.44***
γ₄	-0.2791	-2.20**
γ₅	0.8391	6.78***
γ₆	-0.6660	-5.03***
γ₇	0.2569	2.26**
γ₈	0.0564	0.48
γ₉	-0.4491	-2.95***

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.3726	5.22***
α ARCH Response to squared shocks	0.1108	6.31***
β GARCH Volatility persistence	0.8866	54.77***

γ₁	-0.7486	-4.51***
γ₂	1.3681	4.66***
γ₃	-0.7264	-3.44***
γ₄	-0.2791	-2.20**
γ₅	0.8391	6.78***
γ₆	-0.6660	-5.03***
γ₇	0.2569	2.26**
γ₈	0.0564	0.48
γ₉	-0.4491	-2.95***

V-Lab

Amtech Systems Inc Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Amtech Systems Inc Analyses