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	0.3375	2.00**
αARCH	0.3470	4.88***
βGARCH	0.5012	5.59***

γ₁	-15.6249	-0.72
γ₂	43.2513	1.39
γ₃	-44.1682	-2.47**
γ₄	54.8601	2.62***
γ₅	-88.8768	-3.71***
γ₆	65.5891	3.34***
γ₇	2.0107	0.10
γ₈	-74.8492	-2.20**
γ₉	154.2127	3.13***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.3375	2.00**
α ARCH Response to squared shocks	0.3470	4.88***
β GARCH Volatility persistence	0.5012	5.59***

γ₁	-15.6249	-0.72
γ₂	43.2513	1.39
γ₃	-44.1682	-2.47**
γ₄	54.8601	2.62***
γ₅	-88.8768	-3.71***
γ₆	65.5891	3.34***
γ₇	2.0107	0.10
γ₈	-74.8492	-2.20**
γ₉	154.2127	3.13***

V-Lab

Haoxi Health Technology Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Haoxi Health Technology Ltd Analyses