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	1.3237	1.34
αARCH	0.4814	2.87***
βGARCH	0.3702	4.06***

γ₁	5.9847	1.72*
γ₂	-16.2448	-3.08***
γ₃	19.6025	3.22***
γ₄	-17.2815	-2.04**
γ₅	7.9537	1.09
γ₆	10.5347	2.03**
γ₇	-32.1358	-7.57***
γ₈	42.4025	11.69***
γ₉	-37.3526	-6.32***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3237	1.34
α ARCH Response to squared shocks	0.4814	2.87***
β GARCH Volatility persistence	0.3702	4.06***

γ₁	5.9847	1.72*
γ₂	-16.2448	-3.08***
γ₃	19.6025	3.22***
γ₄	-17.2815	-2.04**
γ₅	7.9537	1.09
γ₆	10.5347	2.03**
γ₇	-32.1358	-7.57***
γ₈	42.4025	11.69***
γ₉	-37.3526	-6.32***

V-Lab

ACS Technologies Limited Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other ACS Technologies Limited Analyses