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	1.0957	3.16***
αARCH	0.1826	20.71***
βGARCH	0.8122	94.95***

γ₁	0.0657	0.32
γ₂	-0.9719	-2.85***
γ₃	3.2071	7.29***
γ₄	-4.0767	-5.88***
γ₅	2.4694	3.27***
γ₆	-2.2493	-3.51***
γ₇	3.6337	7.07***
γ₈	-3.0240	-8.74***
γ₉	1.0609	5.30***
γ₁₀	-0.1504	-0.68

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0957	3.16***
α ARCH Response to squared shocks	0.1826	20.71***
β GARCH Volatility persistence	0.8122	94.95***

γ₁	0.0657	0.32
γ₂	-0.9719	-2.85***
γ₃	3.2071	7.29***
γ₄	-4.0767	-5.88***
γ₅	2.4694	3.27***
γ₆	-2.2493	-3.51***
γ₇	3.6337	7.07***
γ₈	-3.0240	-8.74***
γ₉	1.0609	5.30***
γ₁₀	-0.1504	-0.68

V-Lab

GD Power Development Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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