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	1.8179	2.72***
αARCH	0.5054	8.50***
βGARCH	0.4944	8.31***

γ₁	-1.8834	-0.77
γ₂	10.4145	2.74***
γ₃	-14.9501	-4.48***
γ₄	-2.3270	-0.66
γ₅	18.5394	5.59***
γ₆	-11.2486	-3.62***
γ₇	-3.6094	-0.93
γ₈	16.4100	3.04***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.8179	2.72***
α ARCH Response to squared shocks	0.5054	8.50***
β GARCH Volatility persistence	0.4944	8.31***

γ₁	-1.8834	-0.77
γ₂	10.4145	2.74***
γ₃	-14.9501	-4.48***
γ₄	-2.3270	-0.66
γ₅	18.5394	5.59***
γ₆	-11.2486	-3.62***
γ₇	-3.6094	-0.93
γ₈	16.4100	3.04***

V-Lab

LSE Ventures Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other LSE Ventures Ltd Analyses