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	0.0003	1.75*
αARCH	0.4461	4.80***
βGARCH	0.2217	2.65***

γ₁	-47.4335	-4.16***
γ₂	67.2018	4.38***
γ₃	-23.4367	-2.44**
γ₄	12.5624	1.20
γ₅	-14.9154	-1.57
γ₆	4.1575	0.57
γ₇	-2.1795	-0.32
γ₈	9.3481	1.33
γ₉	-21.2235	-2.90***
γ₁₀	151.7203	24.81***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.0003	1.75*
α ARCH Response to squared shocks	0.4461	4.80***
β GARCH Volatility persistence	0.2217	2.65***

γ₁	-47.4335	-4.16***
γ₂	67.2018	4.38***
γ₃	-23.4367	-2.44**
γ₄	12.5624	1.20
γ₅	-14.9154	-1.57
γ₆	4.1575	0.57
γ₇	-2.1795	-0.32
γ₈	9.3481	1.33
γ₉	-21.2235	-2.90***
γ₁₀	151.7203	24.81***

V-Lab

Semilux International Ltd -Redh Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Semilux International Ltd -Redh Analyses