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	0.7053	3.73***
αARCH	0.2449	2.08**
βGARCH	0.3800	1.91*

γ₁	-27.0173	-1.38
γ₂	37.3734	1.11
γ₃	-27.2926	-1.12
γ₄	39.6251	2.10**
γ₅	-47.8537	-2.74***
γ₆	41.2242	3.31***
γ₇	-20.6748	-2.31**
γ₈	11.9155	1.35
γ₉	-12.1702	-1.55
γ₁₀	-1.1891	-0.10

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.7053	3.73***
α ARCH Response to squared shocks	0.2449	2.08**
β GARCH Volatility persistence	0.3800	1.91*

γ₁	-27.0173	-1.38
γ₂	37.3734	1.11
γ₃	-27.2926	-1.12
γ₄	39.6251	2.10**
γ₅	-47.8537	-2.74***
γ₆	41.2242	3.31***
γ₇	-20.6748	-2.31**
γ₈	11.9155	1.35
γ₉	-12.1702	-1.55
γ₁₀	-1.1891	-0.10

V-Lab

Hedge Recebiveis FII Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Hedge Recebiveis FII Analyses