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	1.3075	1.53
αARCH	0.1437	2.77***
βGARCH	0.8561	16.57***

γ₁	-4.8296	-1.68*
γ₂	7.7238	1.42
γ₃	-0.8338	-0.24
γ₄	-5.1345	-3.80***
γ₅	3.7294	3.07***
γ₆	-0.3155	-0.39
γ₇	-1.0826	-2.06**
γ₈	1.4410	4.26***
γ₉	-1.5240	-4.66***
γ₁₀	2.1564	3.32***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3075	1.53
α ARCH Response to squared shocks	0.1437	2.77***
β GARCH Volatility persistence	0.8561	16.57***

γ₁	-4.8296	-1.68*
γ₂	7.7238	1.42
γ₃	-0.8338	-0.24
γ₄	-5.1345	-3.80***
γ₅	3.7294	3.07***
γ₆	-0.3155	-0.39
γ₇	-1.0826	-2.06**
γ₈	1.4410	4.26***
γ₉	-1.5240	-4.66***
γ₁₀	2.1564	3.32***

V-Lab

Central Finance Co (Lanka) Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Central Finance Co (Lanka) Analyses