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	2.3702	0.03
αARCH	0.2078	0.02
βGARCH	0.7922	0.07

γ₁	-5.8036	-0.03
γ₂	5.7040	0.03
γ₃	2.2133	0.13
γ₄	-3.0893	-0.04
γ₅	1.5730	0.01
γ₆	-7.2097	-0.01
γ₇	10.8771	0.02
γ₈	7.1552	0.01
γ₉	-26.7881	-0.01
γ₁₀	25.3567	0.01

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.3702	0.03
α ARCH Response to squared shocks	0.2078	0.02
β GARCH Volatility persistence	0.7922	0.07

γ₁	-5.8036	-0.03
γ₂	5.7040	0.03
γ₃	2.2133	0.13
γ₄	-3.0893	-0.04
γ₅	1.5730	0.01
γ₆	-7.2097	-0.01
γ₇	10.8771	0.02
γ₈	7.1552	0.01
γ₉	-26.7881	-0.01
γ₁₀	25.3567	0.01

V-Lab

Hanking Gold International Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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