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	1.4616	0.94
αARCH	0.3721	14.19***
βGARCH	0.6267	25.06***

γ₁	-1.3693	-1.39
γ₂	1.1764	0.85
γ₃	1.0677	1.40
γ₄	-3.1682	-4.07***
γ₅	3.9908	4.67***
γ₆	-2.3813	-3.07***
γ₇	1.2115	1.50
γ₈	-0.8577	-0.99
γ₉	1.3676	1.14

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.4616	0.94
α ARCH Response to squared shocks	0.3721	14.19***
β GARCH Volatility persistence	0.6267	25.06***

γ₁	-1.3693	-1.39
γ₂	1.1764	0.85
γ₃	1.0677	1.40
γ₄	-3.1682	-4.07***
γ₅	3.9908	4.67***
γ₆	-2.3813	-3.07***
γ₇	1.2115	1.50
γ₈	-0.8577	-0.99
γ₉	1.3676	1.14

V-Lab

Saif Power Limited Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Saif Power Limited Analyses