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	6.0839
αARCH	0.0827
βGARCH	0.9173

γ₁	0.9006
γ₂	-2.8835
γ₃	2.1643
γ₄	3.0336
γ₅	-6.7511
γ₆	6.2169
γ₇	-6.4326
γ₈	7.3017

Parameter	Value	t-statistic
ω const Unconditional variance weight	6.0839
α ARCH Response to squared shocks	0.0827
β GARCH Volatility persistence	0.9173

γ₁	0.9006
γ₂	-2.8835
γ₃	2.1643
γ₄	3.0336
γ₅	-6.7511
γ₆	6.2169
γ₇	-6.4326
γ₈	7.3017

V-Lab

Quercus Tfi Sa Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Quercus Tfi Sa Analyses