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	0.5457	1.61
αARCH	0.1812	3.56***
βGARCH	0.6872	10.05***

γ₁	7.5360	0.69
γ₂	-25.4259	-1.71*
γ₃	39.3294	5.14***
γ₄	-46.0508	-6.53***
γ₅	42.0007	8.90***
γ₆	-25.5297	-6.72***
γ₇	18.0647	3.42***
γ₈	-10.0909	-1.56
γ₉	-11.9209	-1.36

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.5457	1.61
α ARCH Response to squared shocks	0.1812	3.56***
β GARCH Volatility persistence	0.6872	10.05***

γ₁	7.5360	0.69
γ₂	-25.4259	-1.71*
γ₃	39.3294	5.14***
γ₄	-46.0508	-6.53***
γ₅	42.0007	8.90***
γ₆	-25.5297	-6.72***
γ₇	18.0647	3.42***
γ₈	-10.0909	-1.56
γ₉	-11.9209	-1.36

V-Lab

Hoang MAI Stone Joint Stock Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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