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	0.1666	4.25***
αARCH	0.5190	3.48***
βGARCH	0.0000	0.00

γ₁	0.6898	0.68
γ₂	1.1302	0.61
γ₃	-2.0279	-0.98
γ₄	-4.1623	-2.01**
γ₅	6.4037	4.46***
γ₆	-0.9562	-1.06
γ₇	-3.2522	-5.16***
γ₈	4.6342	9.15***
γ₉	-3.2170	-7.01***
γ₁₀	0.9321	1.48

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.1666	4.25***
α ARCH Response to squared shocks	0.5190	3.48***
β GARCH Volatility persistence	0.0000	0.00

γ₁	0.6898	0.68
γ₂	1.1302	0.61
γ₃	-2.0279	-0.98
γ₄	-4.1623	-2.01**
γ₅	6.4037	4.46***
γ₆	-0.9562	-1.06
γ₇	-3.2522	-5.16***
γ₈	4.6342	9.15***
γ₉	-3.2170	-7.01***
γ₁₀	0.9321	1.48

V-Lab

Dhabriya Polywood Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Dhabriya Polywood Ltd Analyses