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	0.4094	1.06
αARCH	0.1351	1.79*
βGARCH	0.8648	11.43***

γ₁	-7.0991	-0.91
γ₂	16.0966	0.95
γ₃	-7.9960	-0.47
γ₄	1.4820	0.11
γ₅	-12.3214	-2.38**
γ₆	18.0193	3.20***
γ₇	-13.1678	-3.33***
γ₈	5.1842	1.93*
γ₉	0.5518	0.22

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.4094	1.06
α ARCH Response to squared shocks	0.1351	1.79*
β GARCH Volatility persistence	0.8648	11.43***

γ₁	-7.0991	-0.91
γ₂	16.0966	0.95
γ₃	-7.9960	-0.47
γ₄	1.4820	0.11
γ₅	-12.3214	-2.38**
γ₆	18.0193	3.20***
γ₇	-13.1678	-3.33***
γ₈	5.1842	1.93*
γ₉	0.5518	0.22

V-Lab

Trek Metals Limited Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Trek Metals Limited Analyses