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	1.5094	2.72***
αARCH	0.2567	5.55***
βGARCH	0.7432	16.10***

γ₁	-0.7895	-0.74
γ₂	0.6709	0.54
γ₃	0.9588	2.63***
γ₄	-2.0873	-6.47***
γ₅	2.5764	7.80***
γ₆	-3.2368	-9.34***
γ₇	4.1548	7.41***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.5094	2.72***
α ARCH Response to squared shocks	0.2567	5.55***
β GARCH Volatility persistence	0.7432	16.10***

γ₁	-0.7895	-0.74
γ₂	0.6709	0.54
γ₃	0.9588	2.63***
γ₄	-2.0873	-6.47***
γ₅	2.5764	7.80***
γ₆	-3.2368	-9.34***
γ₇	4.1548	7.41***

V-Lab

Quice Food Industries Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Quice Food Industries Ltd Analyses