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	1.0703	4.35***
αARCH	0.2697	2.90***
βGARCH	0.7302	7.83***

γ₁	-0.6436	-1.25
γ₂	3.1523	4.03***
γ₃	-6.6833	-4.20***
γ₄	7.6915	2.62***
γ₅	-5.0205	-2.02**
γ₆	2.0016	2.39**
γ₇	-0.8115	-2.92***
γ₈	0.2689	0.69
γ₉	0.3098	0.60
γ₁₀	-0.5213	-0.91

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0703	4.35***
α ARCH Response to squared shocks	0.2697	2.90***
β GARCH Volatility persistence	0.7302	7.83***

γ₁	-0.6436	-1.25
γ₂	3.1523	4.03***
γ₃	-6.6833	-4.20***
γ₄	7.6915	2.62***
γ₅	-5.0205	-2.02**
γ₆	2.0016	2.39**
γ₇	-0.8115	-2.92***
γ₈	0.2689	0.69
γ₉	0.3098	0.60
γ₁₀	-0.5213	-0.91

V-Lab

SPIC Green Energy Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other SPIC Green Energy Co Ltd Analyses