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	1.0395	0.03
αARCH	0.1932	0.00
βGARCH	0.8067	0.02

γ₁	0.7876	0.00
γ₂	-6.1730	0.00
γ₃	14.8218	0.00
γ₄	-16.8295	0.00
γ₅	11.3470	0.00
γ₆	-5.7748	0.00
γ₇	2.3983	0.01
γ₈	-0.8529	-0.01

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0395	0.03
α ARCH Response to squared shocks	0.1932	0.00
β GARCH Volatility persistence	0.8067	0.02

γ₁	0.7876	0.00
γ₂	-6.1730	0.00
γ₃	14.8218	0.00
γ₄	-16.8295	0.00
γ₅	11.3470	0.00
γ₆	-5.7748	0.00
γ₇	2.3983	0.01
γ₈	-0.8529	-0.01

V-Lab

Km Sugar Mills Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Km Sugar Mills Ltd Analyses