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	2.1344	5.55***
αARCH	0.1306	2.33**
βGARCH	0.7148	5.12***

γ₁	0.1705	1.00
γ₂	-0.3112	-1.10
γ₃	0.3722	1.45
γ₄	-0.3889	-1.25
γ₅	0.1679	0.54
γ₆	-0.2191	-0.86
γ₇	0.8488	4.15***
γ₈	-1.3632	-5.77***
γ₉	1.2678	3.84***

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.1344	5.55***
α ARCH Response to squared shocks	0.1306	2.33**
β GARCH Volatility persistence	0.7148	5.12***

γ₁	0.1705	1.00
γ₂	-0.3112	-1.10
γ₃	0.3722	1.45
γ₄	-0.3889	-1.25
γ₅	0.1679	0.54
γ₆	-0.2191	-0.86
γ₇	0.8488	4.15***
γ₈	-1.3632	-5.77***
γ₉	1.2678	3.84***

V-Lab

Marlin Global Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Marlin Global Ltd Analyses