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	0.2233	3.62***
αARCH	0.2820	2.85***
βGARCH	0.1230	1.64

γ₁	-1.2339	-3.33***
γ₂	1.2617	2.59***
γ₃	0.0278	0.12
γ₄	0.1420	0.66
γ₅	-0.4064	-2.28**
γ₆	0.2453	1.35
γ₇	-0.2741	-0.81
γ₈	0.8651	2.55**
γ₉	-1.4135	-6.04***
γ₁₀	1.5536	6.49***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.2233	3.62***
α ARCH Response to squared shocks	0.2820	2.85***
β GARCH Volatility persistence	0.1230	1.64

γ₁	-1.2339	-3.33***
γ₂	1.2617	2.59***
γ₃	0.0278	0.12
γ₄	0.1420	0.66
γ₅	-0.4064	-2.28**
γ₆	0.2453	1.35
γ₇	-0.2741	-0.81
γ₈	0.8651	2.55**
γ₉	-1.4135	-6.04***
γ₁₀	1.5536	6.49***

V-Lab

Barramundi Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Barramundi Ltd Analyses