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	11.9051	2.80***
αARCH	0.2107	7.82***
βGARCH	0.7860	29.06***

γ₁	0.8385	1.07
γ₂	-0.3197	-0.25
γ₃	-0.1248	-0.16
γ₄	-2.8410	-5.57***
γ₅	5.4704	6.75***
γ₆	-4.7144	-4.12***
γ₇	2.7671	2.71***
γ₈	-2.4620	-3.70***
γ₉	2.5019	3.28***

Parameter	Value	t-statistic
ω const Unconditional variance weight	11.9051	2.80***
α ARCH Response to squared shocks	0.2107	7.82***
β GARCH Volatility persistence	0.7860	29.06***

γ₁	0.8385	1.07
γ₂	-0.3197	-0.25
γ₃	-0.1248	-0.16
γ₄	-2.8410	-5.57***
γ₅	5.4704	6.75***
γ₆	-4.7144	-4.12***
γ₇	2.7671	2.71***
γ₈	-2.4620	-3.70***
γ₉	2.5019	3.28***

V-Lab

Betonjaya Manunggal Tbk Pt Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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