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	4.9812	2.19**
αARCH	0.1439	6.33***
βGARCH	0.7742	27.98***

γ₁	-0.1167	-0.95
γ₂	0.1838	1.07
γ₃	0.0854	1.10
γ₄	-0.2908	-7.72***
γ₅	0.1091	4.51***
γ₆	0.1328	5.79***
γ₇	-0.1969	-8.25***
γ₈	0.2608	7.74***

Parameter	Value	t-statistic
ω const Unconditional variance weight	4.9812	2.19**
α ARCH Response to squared shocks	0.1439	6.33***
β GARCH Volatility persistence	0.7742	27.98***

γ₁	-0.1167	-0.95
γ₂	0.1838	1.07
γ₃	0.0854	1.10
γ₄	-0.2908	-7.72***
γ₅	0.1091	4.51***
γ₆	0.1328	5.79***
γ₇	-0.1969	-8.25***
γ₈	0.2608	7.74***

V-Lab

Vistry Group PLC Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Vistry Group PLC Analyses