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	5.1106	2.27**
αARCH	0.3527	8.28***
βGARCH	0.6468	15.16***

γ₁	-1.8014	-4.76***
γ₂	2.5983	4.90***
γ₃	-0.7596	-2.60***
γ₄	-0.5551	-2.31**
γ₅	1.1001	5.26***
γ₆	-0.9659	-4.87***
γ₇	0.4308	2.76***
γ₈	0.3209	2.26**
γ₉	-1.1537	-6.74***
γ₁₀	1.8357	5.58***

Parameter	Value	t-statistic
ω const Unconditional variance weight	5.1106	2.27**
α ARCH Response to squared shocks	0.3527	8.28***
β GARCH Volatility persistence	0.6468	15.16***

γ₁	-1.8014	-4.76***
γ₂	2.5983	4.90***
γ₃	-0.7596	-2.60***
γ₄	-0.5551	-2.31**
γ₅	1.1001	5.26***
γ₆	-0.9659	-4.87***
γ₇	0.4308	2.76***
γ₈	0.3209	2.26**
γ₉	-1.1537	-6.74***
γ₁₀	1.8357	5.58***

V-Lab

Attock Cement Pakistan Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Attock Cement Pakistan Ltd Analyses