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	0.9336	5.97***
αARCH	0.2509	13.29***
βGARCH	0.7310	40.82***

γ₁	-0.6197	-1.86*
γ₂	1.4379	2.26**
γ₃	-1.5588	-2.18**
γ₄	1.2511	1.79*
γ₅	-1.6152	-2.20**
γ₆	3.1199	2.39**
γ₇	-4.0099	-2.18**
γ₈	3.5647	2.08**
γ₉	-3.0165	-2.27**

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.9336	5.97***
α ARCH Response to squared shocks	0.2509	13.29***
β GARCH Volatility persistence	0.7310	40.82***

γ₁	-0.6197	-1.86*
γ₂	1.4379	2.26**
γ₃	-1.5588	-2.18**
γ₄	1.2511	1.79*
γ₅	-1.6152	-2.20**
γ₆	3.1199	2.39**
γ₇	-4.0099	-2.18**
γ₈	3.5647	2.08**
γ₉	-3.0165	-2.27**

V-Lab

Amana Cooperative Insurance Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Amana Cooperative Insurance Analyses