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	0.6298	3.22***
αARCH	0.0000	0.00
βGARCH	0.9240	10.13***

γ₁	-9.0162	-0.49
γ₂	25.0164	0.80
γ₃	-19.0699	-0.74
γ₄	-3.9475	-0.16
γ₅	50.4361	1.45
γ₆	-156.9731	-3.41***
γ₇	206.7445	4.55***
γ₈	-124.1779	-3.79***
γ₉	37.4730	1.43

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.6298	3.22***
α ARCH Response to squared shocks	0.0000	0.00
β GARCH Volatility persistence	0.9240	10.13***

γ₁	-9.0162	-0.49
γ₂	25.0164	0.80
γ₃	-19.0699	-0.74
γ₄	-3.9475	-0.16
γ₅	50.4361	1.45
γ₆	-156.9731	-3.41***
γ₇	206.7445	4.55***
γ₈	-124.1779	-3.79***
γ₉	37.4730	1.43

V-Lab

Mokingran Jewellery Group Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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