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	0.6951	3.78***
αARCH	0.0487	2.88***
βGARCH	0.8999	21.97***

γ₁	-0.0713	-0.29
γ₂	-0.0806	-0.21
γ₃	-0.0604	-0.19
γ₄	0.8084	2.82***
γ₅	-0.4818	-1.29
γ₆	-0.9335	-1.95*
γ₇	1.5264	3.39***
γ₈	-1.9327	-4.53***
γ₉	2.9542	5.96***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.6951	3.78***
α ARCH Response to squared shocks	0.0487	2.88***
β GARCH Volatility persistence	0.8999	21.97***

γ₁	-0.0713	-0.29
γ₂	-0.0806	-0.21
γ₃	-0.0604	-0.19
γ₄	0.8084	2.82***
γ₅	-0.4818	-1.29
γ₆	-0.9335	-1.95*
γ₇	1.5264	3.39***
γ₈	-1.9327	-4.53***
γ₉	2.9542	5.96***

V-Lab

Filtisac SA Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Filtisac SA Analyses