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	0.0154	0.06
αARCH	0.0000	0.00
βGARCH	0.9994	0.32

γ₁	-2,234.5874	-0.24
γ₂	3,058.9606	0.92
γ₃	-1,184.0932	-0.64
γ₄	628.8650	0.51
γ₅	-358.4136	-0.45
γ₆	95.0084	0.17
γ₇	18.0357	0.04

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.0154	0.06
α ARCH Response to squared shocks	0.0000	0.00
β GARCH Volatility persistence	0.9994	0.32

γ₁	-2,234.5874	-0.24
γ₂	3,058.9606	0.92
γ₃	-1,184.0932	-0.64
γ₄	628.8650	0.51
γ₅	-358.4136	-0.45
γ₆	95.0084	0.17
γ₇	18.0357	0.04

V-Lab

Pasqal Holding SA Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Pasqal Holding SA Analyses