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	0.2770	3.00***
αARCH	0.0337	1.62
βGARCH	0.7551	6.18***

γ₁	-3.5942	-4.04***
γ₂	4.0823	2.92***
γ₃	0.8765	0.62
γ₄	-2.8311	-1.53
γ₅	-1.7203	-0.67
γ₆	8.6462	3.55***
γ₇	-9.9381	-7.21***
γ₈	7.1592	2.61***
γ₉	-2.0532	-0.54

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.2770	3.00***
α ARCH Response to squared shocks	0.0337	1.62
β GARCH Volatility persistence	0.7551	6.18***

γ₁	-3.5942	-4.04***
γ₂	4.0823	2.92***
γ₃	0.8765	0.62
γ₄	-2.8311	-1.53
γ₅	-1.7203	-0.67
γ₆	8.6462	3.55***
γ₇	-9.9381	-7.21***
γ₈	7.1592	2.61***
γ₉	-2.0532	-0.54

V-Lab

Soho Holly Futures Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Soho Holly Futures Co Ltd Analyses