How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

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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	1.5719	3.81***
αARCH	0.1843	3.90***
βGARCH	0.6845	12.06***

γ₁	2.0300	3.15***
γ₂	-2.8154	-2.72***
γ₃	1.6784	2.34**
γ₄	-1.8037	-2.42**
γ₅	1.2965	1.67*
γ₆	-0.3736	-0.47
γ₇	1.0414	0.77
γ₈	-2.0361	-0.84
γ₉	-0.7893	-0.22

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.5719	3.81***
α ARCH Response to squared shocks	0.1843	3.90***
β GARCH Volatility persistence	0.6845	12.06***

γ₁	2.0300	3.15***
γ₂	-2.8154	-2.72***
γ₃	1.6784	2.34**
γ₄	-1.8037	-2.42**
γ₅	1.2965	1.67*
γ₆	-0.3736	-0.47
γ₇	1.0414	0.77
γ₈	-2.0361	-0.84
γ₉	-0.7893	-0.22

V-Lab

Naos Emerging Opportunities Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Naos Emerging Opportunities Co Ltd Analyses