How volatility evolves over time

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{name} Model Equation

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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	0.6161	4.27***
αARCH	0.2357	19.97***
βGARCH	0.7633	64.64***

γ₁	0.1774	0.86
γ₂	-0.7337	-2.35**
γ₃	2.1143	8.68***
γ₄	-2.8713	-8.66***
γ₅	1.8335	4.40***
γ₆	-2.2445	-5.30***
γ₇	4.3077	9.42***
γ₈	-3.8691	-10.55***
γ₉	1.4975	6.24***
γ₁₀	-0.3323	-1.17

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.6161	4.27***
α ARCH Response to squared shocks	0.2357	19.97***
β GARCH Volatility persistence	0.7633	64.64***

γ₁	0.1774	0.86
γ₂	-0.7337	-2.35**
γ₃	2.1143	8.68***
γ₄	-2.8713	-8.66***
γ₅	1.8335	4.40***
γ₆	-2.2445	-5.30***
γ₇	4.3077	9.42***
γ₈	-3.8691	-10.55***
γ₉	1.4975	6.24***
γ₁₀	-0.3323	-1.17

V-Lab

Guangzhou Development Group Inc Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Guangzhou Development Group Inc Analyses