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	0.5638	1.26
αARCH	0.2648	7.57***
βGARCH	0.7330	20.94***

γ₁	-12.0131	-2.23**
γ₂	19.4533	2.39**
γ₃	-10.4439	-1.56
γ₄	-2.0231	-0.26
γ₅	14.0512	2.26**
γ₆	-19.5570	-4.92***
γ₇	18.8724	5.72***
γ₈	-9.6122	-2.10**
γ₉	-2.3188	-0.41
γ₁₀	-2.2403	-0.31

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.5638	1.26
α ARCH Response to squared shocks	0.2648	7.57***
β GARCH Volatility persistence	0.7330	20.94***

γ₁	-12.0131	-2.23**
γ₂	19.4533	2.39**
γ₃	-10.4439	-1.56
γ₄	-2.0231	-0.26
γ₅	14.0512	2.26**
γ₆	-19.5570	-4.92***
γ₇	18.8724	5.72***
γ₈	-9.6122	-2.10**
γ₉	-2.3188	-0.41
γ₁₀	-2.2403	-0.31

V-Lab

Indonesia Prima Prop (Pt) Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Indonesia Prima Prop (Pt) Analyses