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	1.1901	3.79***
αARCH	0.1991	6.93***
βGARCH	0.7997	28.04***

γ₁	-0.8732	-1.88*
γ₂	1.3683	1.79*
γ₃	-3.8313	-2.72***
γ₄	9.0227	3.32***
γ₅	-8.9533	-3.63***
γ₆	4.0583	4.27***
γ₇	-1.3616	-4.41***
γ₈	1.2414	3.60***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1901	3.79***
α ARCH Response to squared shocks	0.1991	6.93***
β GARCH Volatility persistence	0.7997	28.04***

γ₁	-0.8732	-1.88*
γ₂	1.3683	1.79*
γ₃	-3.8313	-2.72***
γ₄	9.0227	3.32***
γ₅	-8.9533	-3.63***
γ₆	4.0583	4.27***
γ₇	-1.3616	-4.41***
γ₈	1.2414	3.60***

V-Lab

JPMorgan UK Small CAP Growth & Income PLC Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other JPMorgan UK Small CAP Growth & Income PLC Analyses