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	1.3646	3.80***
αARCH	0.2295	8.66***
βGARCH	0.7693	29.34***

γ₁	-1.0022	-4.13***
γ₂	1.7721	4.46***
γ₃	-2.7457	-6.23***
γ₄	4.6994	7.11***
γ₅	-3.7744	-6.55***
γ₆	0.7934	2.66***
γ₇	0.4288	2.82***
γ₈	-0.2531	-2.48**
γ₉	0.1940	1.31

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3646	3.80***
α ARCH Response to squared shocks	0.2295	8.66***
β GARCH Volatility persistence	0.7693	29.34***

γ₁	-1.0022	-4.13***
γ₂	1.7721	4.46***
γ₃	-2.7457	-6.23***
γ₄	4.6994	7.11***
γ₅	-3.7744	-6.55***
γ₆	0.7934	2.66***
γ₇	0.4288	2.82***
γ₈	-0.2531	-2.48**
γ₉	0.1940	1.31

V-Lab

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Date Range:

News Impact Curve

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