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

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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	0.5890	0.78
αARCH	0.1274	4.31***
βGARCH	0.8720	30.28***

γ₁	-2.4773	-0.66
γ₂	8.1676	1.08
γ₃	-11.5732	-1.43
γ₄	8.1423	1.37
γ₅	0.8373	0.15
γ₆	-5.3322	-0.86
γ₇	0.7723	0.27
γ₈	4.2799	3.36***
γ₉	-6.0225	-3.76***
γ₁₀	7.6689	2.99***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.5890	0.78
α ARCH Response to squared shocks	0.1274	4.31***
β GARCH Volatility persistence	0.8720	30.28***

γ₁	-2.4773	-0.66
γ₂	8.1676	1.08
γ₃	-11.5732	-1.43
γ₄	8.1423	1.37
γ₅	0.8373	0.15
γ₆	-5.3322	-0.86
γ₇	0.7723	0.27
γ₈	4.2799	3.36***
γ₉	-6.0225	-3.76***
γ₁₀	7.6689	2.99***

V-Lab

Kore Potash plc Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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