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	1.4293	2.15**
αARCH	0.2319	9.53***
βGARCH	0.7610	33.60***

γ₁	-0.9814	-1.16
γ₂	0.0003	0.00
γ₃	2.2313	2.73***
γ₄	-1.9761	-3.04***
γ₅	1.3948	1.70*
γ₆	-1.0809	-1.42
γ₇	0.9344	1.37
γ₈	-1.4538	-2.12**
γ₉	2.3017	2.87***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.4293	2.15**
α ARCH Response to squared shocks	0.2319	9.53***
β GARCH Volatility persistence	0.7610	33.60***

γ₁	-0.9814	-1.16
γ₂	0.0003	0.00
γ₃	2.2313	2.73***
γ₄	-1.9761	-3.04***
γ₅	1.3948	1.70*
γ₆	-1.0809	-1.42
γ₇	0.9344	1.37
γ₈	-1.4538	-2.12**
γ₉	2.3017	2.87***

V-Lab

Kse Ltd. Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Kse Ltd. Analyses