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	1.0403	2.24**
αARCH	0.2451	5.95***
βGARCH	0.7527	18.28***

γ₁	1.4738	0.34
γ₂	-2.5342	-0.35
γ₃	-8.7153	-1.18
γ₄	35.1623	2.63***
γ₅	-63.1065	-3.01***
γ₆	72.4828	3.19***
γ₇	-48.8584	-3.21***
γ₈	16.7222	2.89***
γ₉	-7.1164	-1.53

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0403	2.24**
α ARCH Response to squared shocks	0.2451	5.95***
β GARCH Volatility persistence	0.7527	18.28***

γ₁	1.4738	0.34
γ₂	-2.5342	-0.35
γ₃	-8.7153	-1.18
γ₄	35.1623	2.63***
γ₅	-63.1065	-3.01***
γ₆	72.4828	3.19***
γ₇	-48.8584	-3.21***
γ₈	16.7222	2.89***
γ₉	-7.1164	-1.53

V-Lab

Akshar Spintex Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Akshar Spintex Ltd Analyses