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	0.8453	3.38***
αARCH	0.0229	2.67***
βGARCH	0.9590	45.56***

γ₁	-0.5555	-0.85
γ₂	0.6391	0.66
γ₃	1.2257	2.09**
γ₄	-2.5539	-4.41***
γ₅	1.5860	2.30**
γ₆	-0.2269	-0.21
γ₇	-1.0705	-0.69
γ₈	1.5333	1.08
γ₉	-1.3465	-1.03

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.8453	3.38***
α ARCH Response to squared shocks	0.0229	2.67***
β GARCH Volatility persistence	0.9590	45.56***

γ₁	-0.5555	-0.85
γ₂	0.6391	0.66
γ₃	1.2257	2.09**
γ₄	-2.5539	-4.41***
γ₅	1.5860	2.30**
γ₆	-0.2269	-0.21
γ₇	-1.0705	-0.69
γ₈	1.5333	1.08
γ₉	-1.3465	-1.03

V-Lab

Servair Abidjan Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Servair Abidjan Analyses