How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

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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	0.7410	3.03***
αARCH	0.1600	2.27**
βGARCH	0.8398	11.94***

γ₁	0.5809	0.29
γ₂	-3.6128	-1.16
γ₃	6.3543	3.77***
γ₄	-8.5347	-10.85***
γ₅	10.2948	12.31***
γ₆	-8.0113	-5.22***
γ₇	3.7427	1.32
γ₈	-1.1460	-0.31
γ₉	2.8263	0.80
γ₁₀	-0.0796	-0.01

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.7410	3.03***
α ARCH Response to squared shocks	0.1600	2.27**
β GARCH Volatility persistence	0.8398	11.94***

γ₁	0.5809	0.29
γ₂	-3.6128	-1.16
γ₃	6.3543	3.77***
γ₄	-8.5347	-10.85***
γ₅	10.2948	12.31***
γ₆	-8.0113	-5.22***
γ₇	3.7427	1.32
γ₈	-1.1460	-0.31
γ₉	2.8263	0.80
γ₁₀	-0.0796	-0.01

V-Lab

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