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	0.0242	0.05
αARCH	0.0000	0.00
βGARCH	0.9997	0.26

γ₁	-1,481.1162	-0.27
γ₂	1,968.3197	1.27
γ₃	-657.4121	-0.78
γ₄	335.3756	0.43
γ₅	-244.5614	-0.47
γ₆	85.9901	0.18
γ₇	24.1655	0.08

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.0242	0.05
α ARCH Response to squared shocks	0.0000	0.00
β GARCH Volatility persistence	0.9997	0.26

γ₁	-1,481.1162	-0.27
γ₂	1,968.3197	1.27
γ₃	-657.4121	-0.78
γ₄	335.3756	0.43
γ₅	-244.5614	-0.47
γ₆	85.9901	0.18
γ₇	24.1655	0.08

V-Lab

Pasqal Holding SA Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Pasqal Holding SA Analyses