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	7.2872	3.49***
αARCH	0.8187	83.12***
βGARCH	0.1811	18.37***

γ₁	-1.0291	-1.55
γ₂	2.1383	2.41**
γ₃	-1.9551	-5.33***
γ₄	1.3338	4.32***
γ₅	-19.6145	-6.71***
γ₆	66.3940	7.07***
γ₇	-128.9338	-10.22***
γ₈	186.6261	14.89***
γ₉	-179.4982	-11.80***
γ₁₀	126.9860	6.67***

Parameter	Value	t-statistic
ω const Unconditional variance weight	7.2872	3.49***
α ARCH Response to squared shocks	0.8187	83.12***
β GARCH Volatility persistence	0.1811	18.37***

γ₁	-1.0291	-1.55
γ₂	2.1383	2.41**
γ₃	-1.9551	-5.33***
γ₄	1.3338	4.32***
γ₅	-19.6145	-6.71***
γ₆	66.3940	7.07***
γ₇	-128.9338	-10.22***
γ₈	186.6261	14.89***
γ₉	-179.4982	-11.80***
γ₁₀	126.9860	6.67***

V-Lab

Power Grid Co Of Bangladesh Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Power Grid Co Of Bangladesh Analyses