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	1.0103	0.83
αARCH	0.1636	7.42***
βGARCH	0.8355	38.85***

γ₁	-0.1300	-1.18
γ₂	0.0688	0.41
γ₃	0.0275	0.23
γ₄	0.2019	1.29
γ₅	-0.3688	-2.07**
γ₆	0.3667	2.25**
γ₇	-0.3820	-1.26
γ₈	0.5656	1.01

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0103	0.83
α ARCH Response to squared shocks	0.1636	7.42***
β GARCH Volatility persistence	0.8355	38.85***

γ₁	-0.1300	-1.18
γ₂	0.0688	0.41
γ₃	0.0275	0.23
γ₄	0.2019	1.29
γ₅	-0.3688	-2.07**
γ₆	0.3667	2.25**
γ₇	-0.3820	-1.26
γ₈	0.5656	1.01

V-Lab

Fraser & Neave Holdings Bhd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Fraser & Neave Holdings Bhd Analyses