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	2.5522	3.88***
αARCH	0.2162	8.50***
βGARCH	0.7241	20.91***

γ₁	0.0013	0.00
γ₂	-0.3736	-0.28
γ₃	2.3112	2.97***
γ₄	-3.8053	-5.58***
γ₅	3.1705	3.82***
γ₆	-3.5527	-3.51***
γ₇	4.3277	3.98***
γ₈	-4.2796	-3.17***

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.5522	3.88***
α ARCH Response to squared shocks	0.2162	8.50***
β GARCH Volatility persistence	0.7241	20.91***

γ₁	0.0013	0.00
γ₂	-0.3736	-0.28
γ₃	2.3112	2.97***
γ₄	-3.8053	-5.58***
γ₅	3.1705	3.82***
γ₆	-3.5527	-3.51***
γ₇	4.3277	3.98***
γ₈	-4.2796	-3.17***

V-Lab

Janana DE Malucho Textile Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Janana DE Malucho Textile Analyses