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	7.2693	1.74*
αARCH	0.3282	4.69***
βGARCH	0.4462	5.57***

γ₁	1.7627	4.38***
γ₂	-0.3755	-0.39
γ₃	-2.3608	-2.38**
γ₄	1.3457	1.82*
γ₅	0.1993	0.36
γ₆	-2.1229	-1.45
γ₇	2.2856	1.07
γ₈	-0.8352	-0.51
γ₉	0.9721	0.69
γ₁₀	-0.7432	-0.40

Parameter	Value	t-statistic
ω const Unconditional variance weight	7.2693	1.74*
α ARCH Response to squared shocks	0.3282	4.69***
β GARCH Volatility persistence	0.4462	5.57***

γ₁	1.7627	4.38***
γ₂	-0.3755	-0.39
γ₃	-2.3608	-2.38**
γ₄	1.3457	1.82*
γ₅	0.1993	0.36
γ₆	-2.1229	-1.45
γ₇	2.2856	1.07
γ₈	-0.8352	-0.51
γ₉	0.9721	0.69
γ₁₀	-0.7432	-0.40

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Shanghai LongYun Media Group Co., Ltd. Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Shanghai LongYun Media Group Co., Ltd. Analyses