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	1.9394	1.62
αARCH	0.1427	3.36***
βGARCH	0.7878	12.57***

γ₁	-22.3307	-2.53**
γ₂	38.1644	2.81***
γ₃	-20.5477	-2.85***
γ₄	4.3780	1.21
γ₅	-0.5916	-0.15
γ₆	4.9485	0.98
γ₇	-6.9710	-1.82*
γ₈	2.8338	1.17
γ₉	1.7267	0.85
γ₁₀	-2.7498	-1.16

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.9394	1.62
α ARCH Response to squared shocks	0.1427	3.36***
β GARCH Volatility persistence	0.7878	12.57***

γ₁	-22.3307	-2.53**
γ₂	38.1644	2.81***
γ₃	-20.5477	-2.85***
γ₄	4.3780	1.21
γ₅	-0.5916	-0.15
γ₆	4.9485	0.98
γ₇	-6.9710	-1.82*
γ₈	2.8338	1.17
γ₉	1.7267	0.85
γ₁₀	-2.7498	-1.16

V-Lab

Youngqin Intl Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Youngqin Intl Co Ltd Analyses