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	1.1814	4.39***
αARCH	0.1950	14.99***
βGARCH	0.8036	58.35***

γ₁	-0.3933	-4.10***
γ₂	0.6424	4.26***
γ₃	-0.4778	-4.16***
γ₄	0.4837	5.30***
γ₅	-0.6899	-9.04***
γ₆	1.1514	9.92***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1814	4.39***
α ARCH Response to squared shocks	0.1950	14.99***
β GARCH Volatility persistence	0.8036	58.35***

γ₁	-0.3933	-4.10***
γ₂	0.6424	4.26***
γ₃	-0.4778	-4.16***
γ₄	0.4837	5.30***
γ₅	-0.6899	-9.04***
γ₆	1.1514	9.92***

V-Lab

Uniform Industrial Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Uniform Industrial Analyses