How volatility evolves over time

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{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	1.6521	3.50***
αARCH	0.2605	9.79***
βGARCH	0.7378	27.49***

γ₁	-2.8116	-3.19***
γ₂	3.4815	2.60***
γ₃	-4.9384	-2.42**
γ₄	13.7803	2.83***
γ₅	-16.7674	-2.81***
γ₆	10.7774	2.75***
γ₇	-12.7073	-2.93***
γ₈	21.8431	2.16**
γ₉	-18.9615	-1.97**
γ₁₀	9.2701	2.47**

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.6521	3.50***
α ARCH Response to squared shocks	0.2605	9.79***
β GARCH Volatility persistence	0.7378	27.49***

γ₁	-2.8116	-3.19***
γ₂	3.4815	2.60***
γ₃	-4.9384	-2.42**
γ₄	13.7803	2.83***
γ₅	-16.7674	-2.81***
γ₆	10.7774	2.75***
γ₇	-12.7073	-2.93***
γ₈	21.8431	2.16**
γ₉	-18.9615	-1.97**
γ₁₀	9.2701	2.47**

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Inversora Juramento Sa Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Inversora Juramento Sa Analyses