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	1.9595	1.64
αARCH	0.1444	3.40***
βGARCH	0.7882	12.82***

γ₁	-22.2260	-2.53**
γ₂	38.1302	2.80***
γ₃	-20.7546	-2.85***
γ₄	4.4820	1.26
γ₅	-0.3264	-0.08
γ₆	4.5238	0.90
γ₇	-6.8438	-1.76*
γ₈	3.1011	1.26
γ₉	1.3828	0.66
γ₁₀	-2.4099	-1.02

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.9595	1.64
α ARCH Response to squared shocks	0.1444	3.40***
β GARCH Volatility persistence	0.7882	12.82***

γ₁	-22.2260	-2.53**
γ₂	38.1302	2.80***
γ₃	-20.7546	-2.85***
γ₄	4.4820	1.26
γ₅	-0.3264	-0.08
γ₆	4.5238	0.90
γ₇	-6.8438	-1.76*
γ₈	3.1011	1.26
γ₉	1.3828	0.66
γ₁₀	-2.4099	-1.02

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