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	0.3792	3.48***
αARCH	0.0701	3.45***
βGARCH	0.8380	14.25***

γ₁	-1.1507	-0.22
γ₂	-4.5003	-0.51
γ₃	9.0935	1.21
γ₄	-1.3412	-0.18
γ₅	-8.6841	-1.22
γ₆	16.4792	2.58***
γ₇	-23.4160	-4.53***
γ₈	26.1011	4.13***
γ₉	-22.6711	-3.40***
γ₁₀	6.6507	0.91

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.3792	3.48***
α ARCH Response to squared shocks	0.0701	3.45***
β GARCH Volatility persistence	0.8380	14.25***

γ₁	-1.1507	-0.22
γ₂	-4.5003	-0.51
γ₃	9.0935	1.21
γ₄	-1.3412	-0.18
γ₅	-8.6841	-1.22
γ₆	16.4792	2.58***
γ₇	-23.4160	-4.53***
γ₈	26.1011	4.13***
γ₉	-22.6711	-3.40***
γ₁₀	6.6507	0.91

V-Lab

SANVO Fine Chemicals Group Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other SANVO Fine Chemicals Group Ltd Analyses