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	1.3994	4.08***
αARCH	0.1867	10.70***
βGARCH	0.8131	46.17***

γ₁	-0.1733	-0.19
γ₂	0.8240	0.65
γ₃	-1.3182	-1.58
γ₄	1.0141	2.03**
γ₅	-0.8728	-3.61***
γ₆	1.2736	5.66***
γ₇	-1.4581	-5.54***
γ₈	1.4672	5.18***
γ₉	-2.4352	-5.59***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3994	4.08***
α ARCH Response to squared shocks	0.1867	10.70***
β GARCH Volatility persistence	0.8131	46.17***

γ₁	-0.1733	-0.19
γ₂	0.8240	0.65
γ₃	-1.3182	-1.58
γ₄	1.0141	2.03**
γ₅	-0.8728	-3.61***
γ₆	1.2736	5.66***
γ₇	-1.4581	-5.54***
γ₈	1.4672	5.18***
γ₉	-2.4352	-5.59***

V-Lab

Tri-Pack Films Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Tri-Pack Films Analyses