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	0.1695	2.39**
αARCH	0.0831	4.63***
βGARCH	0.8403	21.90***

γ₁	-0.7967	-1.94*
γ₂	0.6268	1.18
γ₃	-0.1315	-0.53
γ₄	0.7390	2.59***
γ₅	-0.6699	-1.91*
γ₆	0.5201	1.44
γ₇	-0.8473	-3.05***
γ₈	1.0444	4.74***
γ₉	-0.8144	-4.94***
γ₁₀	1.1387	6.12***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.1695	2.39**
α ARCH Response to squared shocks	0.0831	4.63***
β GARCH Volatility persistence	0.8403	21.90***

γ₁	-0.7967	-1.94*
γ₂	0.6268	1.18
γ₃	-0.1315	-0.53
γ₄	0.7390	2.59***
γ₅	-0.6699	-1.91*
γ₆	0.5201	1.44
γ₇	-0.8473	-3.05***
γ₈	1.0444	4.74***
γ₉	-0.8144	-4.94***
γ₁₀	1.1387	6.12***

V-Lab

Afrimat Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Afrimat Ltd Analyses