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

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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	11.4747	1.70*
αARCH	0.3406	6.09***
βGARCH	0.6373	18.50***

γ₁	-0.6501	-0.53
γ₂	2.4103	1.40
γ₃	-18.1392	-5.73***
γ₄	34.5280	4.02***
γ₅	-7.5224	-0.81
γ₆	-29.1873	-3.69***
γ₇	27.1728	5.25***
γ₈	-13.1090	-4.99***
γ₉	4.9901	3.00***
γ₁₀	0.1755	0.10

Parameter	Value	t-statistic
ω const Unconditional variance weight	11.4747	1.70*
α ARCH Response to squared shocks	0.3406	6.09***
β GARCH Volatility persistence	0.6373	18.50***

γ₁	-0.6501	-0.53
γ₂	2.4103	1.40
γ₃	-18.1392	-5.73***
γ₄	34.5280	4.02***
γ₅	-7.5224	-0.81
γ₆	-29.1873	-3.69***
γ₇	27.1728	5.25***
γ₈	-13.1090	-4.99***
γ₉	4.9901	3.00***
γ₁₀	0.1755	0.10

V-Lab

Quercus Tfi Sa Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Quercus Tfi Sa Analyses