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	0.5304	1.19
αARCH	0.0993	5.92***
βGARCH	0.8768	43.39***

γ₁	-0.7457	-2.42**
γ₂	1.0857	2.79***
γ₃	-0.5409	-3.27***
γ₄	0.2954	1.93*
γ₅	-0.2477	-1.82*
γ₆	0.1770	1.42
γ₇	0.1229	1.02
γ₈	-0.1720	-1.61
γ₉	-0.0259	-0.22

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.5304	1.19
α ARCH Response to squared shocks	0.0993	5.92***
β GARCH Volatility persistence	0.8768	43.39***

γ₁	-0.7457	-2.42**
γ₂	1.0857	2.79***
γ₃	-0.5409	-3.27***
γ₄	0.2954	1.93*
γ₅	-0.2477	-1.82*
γ₆	0.1770	1.42
γ₇	0.1229	1.02
γ₈	-0.1720	-1.61
γ₉	-0.0259	-0.22

V-Lab

Itausa SA Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Itausa SA Analyses