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	0.2206	0.68
αARCH	0.6242	10.65***
βGARCH	0.3754	32.44***

γ₁	-161.0326	-0.43
γ₂	643.0154	1.02
γ₃	-2,002.8636	-6.19***
γ₄	4,421.5578	93.67***
γ₅	-5,336.2197	-226.15***
γ₆	3,309.0296	99.44***
γ₇	-1,173.1824	-19.07***
γ₈	578.4768	4.86***
γ₉	-413.0539	-3.95***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.2206	0.68
α ARCH Response to squared shocks	0.6242	10.65***
β GARCH Volatility persistence	0.3754	32.44***

γ₁	-161.0326	-0.43
γ₂	643.0154	1.02
γ₃	-2,002.8636	-6.19***
γ₄	4,421.5578	93.67***
γ₅	-5,336.2197	-226.15***
γ₆	3,309.0296	99.44***
γ₇	-1,173.1824	-19.07***
γ₈	578.4768	4.86***
γ₉	-413.0539	-3.95***

V-Lab

Pt Cilacap Samudera Fishing Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Pt Cilacap Samudera Fishing Analyses