V-Lab
Pasqal Holding SA APARCH Volatility Analysis
High-persistence model: shocks decay very slowly, so the theoretical long-run value may not be practically meaningful
Volatility prediction for Monday, August 31st, 2026
1 Day
429.09%
1 Week
430.43%
1 Month
435.81%
Analysis last updated: Sunday, August 30, 2026 at 03:33 PM UTC
News Impact Curve
How returns affect tomorrow's volatilityVolatility Forecast
How volatility evolves over timeParameter Estimates
Jan 8, 2026 to Aug 28, 2026Model Insight
Estimated persistence of 1.000 is at or above 1 (non-stationary): volatility shocks do not decay and the long-run variance is undefined, so long-horizon forecasts should be treated with caution. The volatility power δ = 1.56 sits below 2, so large shocks influence volatility less than quadratically, a more outlier-robust response than standard GARCH.
APARCH Model
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| Param | Value | t-stat |
|---|---|---|
| ωconst | 0.4220 | 0.71 |
| αARCH | 0.8935 | 0.19 |
| βGARCH | 0.1065 | 0.10 |
| γleverage | 0.5714 | 1.02 |
| δpower | 1.5611 | 0.32 |
1.000
Persistence-
Half-lifeAPARCH Model
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| Parameter | Value | t-statistic |
|---|---|---|
ω const Unconditional variance weight | 0.4220 | 0.71 |
α ARCH Response to squared shocks | 0.8935 | 0.19 |
β GARCH Volatility persistence | 0.1065 | 0.10 |
γ leverage Additional response to negative shocks | 0.5714 | 1.02 |
δ power Transformation power | 1.5611 | 0.32 |
Persistence:
1.000
Half-life:
-
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