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	0.2255	3.63***
αARCH	0.2913	2.91***
βGARCH	0.1294	1.73*

γ₁	-1.2253	-3.35***
γ₂	1.2549	2.60***
γ₃	0.0258	0.12
γ₄	0.1434	0.65
γ₅	-0.4139	-2.19**
γ₆	0.2513	1.54
γ₇	-0.2542	-0.80
γ₈	0.8205	2.48**
γ₉	-1.3882	-5.96***
γ₁₀	1.6230	6.88***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.2255	3.63***
α ARCH Response to squared shocks	0.2913	2.91***
β GARCH Volatility persistence	0.1294	1.73*

γ₁	-1.2253	-3.35***
γ₂	1.2549	2.60***
γ₃	0.0258	0.12
γ₄	0.1434	0.65
γ₅	-0.4139	-2.19**
γ₆	0.2513	1.54
γ₇	-0.2542	-0.80
γ₈	0.8205	2.48**
γ₉	-1.3882	-5.96***
γ₁₀	1.6230	6.88***

V-Lab

Barramundi Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Barramundi Ltd Analyses