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	0.8109	5.14***
αARCH	0.2942	3.74***
βGARCH	0.7056	8.97***

γ₁	2.4690	1.69*
γ₂	-4.0049	-2.04**
γ₃	0.7216	0.99
γ₄	2.5365	4.20***
γ₅	-5.8888	-7.54***
γ₆	8.7436	13.17***
γ₇	-5.2109	-8.07***
γ₈	-1.5251	-2.47**
γ₉	3.9275	2.80***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.8109	5.14***
α ARCH Response to squared shocks	0.2942	3.74***
β GARCH Volatility persistence	0.7056	8.97***

γ₁	2.4690	1.69*
γ₂	-4.0049	-2.04**
γ₃	0.7216	0.99
γ₄	2.5365	4.20***
γ₅	-5.8888	-7.54***
γ₆	8.7436	13.17***
γ₇	-5.2109	-8.07***
γ₈	-1.5251	-2.47**
γ₉	3.9275	2.80***

V-Lab

Supra Boga Lestari Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Supra Boga Lestari Analyses