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	3.8615	1.85*
αARCH	0.2243	8.82***
βGARCH	0.7752	30.51***

γ₁	-0.2267	-0.28
γ₂	-1.2404	-0.72
γ₃	6.1220	1.18
γ₄	-10.6958	-1.37
γ₅	11.5731	1.61
γ₆	-8.2766	-1.82*
γ₇	2.9492	1.87*
γ₈	-0.3660	-0.86
γ₉	0.5667	0.73

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.8615	1.85*
α ARCH Response to squared shocks	0.2243	8.82***
β GARCH Volatility persistence	0.7752	30.51***

γ₁	-0.2267	-0.28
γ₂	-1.2404	-0.72
γ₃	6.1220	1.18
γ₄	-10.6958	-1.37
γ₅	11.5731	1.61
γ₆	-8.2766	-1.82*
γ₇	2.9492	1.87*
γ₈	-0.3660	-0.86
γ₉	0.5667	0.73

V-Lab

Hunt Electronic Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Hunt Electronic Co Ltd Analyses