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	3.5574	2.98***
αARCH	0.1998	6.80***
βGARCH	0.7029	17.92***

γ₁	-5.2328	-3.22***
γ₂	10.8115	4.56***
γ₃	-7.9099	-5.41***
γ₄	3.3286	3.24***
γ₅	-0.5075	-0.53
γ₆	-0.6583	-0.55
γ₇	1.1880	0.68

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.5574	2.98***
α ARCH Response to squared shocks	0.1998	6.80***
β GARCH Volatility persistence	0.7029	17.92***

γ₁	-5.2328	-3.22***
γ₂	10.8115	4.56***
γ₃	-7.9099	-5.41***
γ₄	3.3286	3.24***
γ₅	-0.5075	-0.53
γ₆	-0.6583	-0.55
γ₇	1.1880	0.68

V-Lab

FII Vida Nova Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other FII Vida Nova Analyses