V-Lab
Nodestream Ltd APARCH Volatility Analysis
High-persistence model: shocks decay very slowly, so the theoretical long-run value may not be practically meaningful
Volatility prediction for Friday, September 11th, 2026
1 Day
136.82%
1 Week
136.88%
1 Month
137.12%
Analysis last updated: Friday, September 11, 2026 at 05:55 PM UTC
News Impact Curve
How returns affect tomorrow's volatilityVolatility Forecast
How volatility evolves over timeParameter Estimates
May 12, 2016 to Sep 4, 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 = 2.35 sits above 2, so large shocks influence volatility more than quadratically, dominating the response more than in standard GARCH.
APARCH Model
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| Param | Value | t-stat |
|---|---|---|
| ωconst | 0.0808 | 0.35 |
| αARCH | 0.0038 | 0.00 |
| βGARCH | 0.9890 | 273.66*** |
| γleverage | 1.0000 | 0.00 |
| δpower | 2.3474 | 2.33** |
1.000
Persistence-
Half-lifeAPARCH Model
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| Parameter | Value | t-statistic |
|---|---|---|
ω const Unconditional variance weight | 0.0808 | 0.35 |
α ARCH Response to squared shocks | 0.0038 | 0.00 |
β GARCH Volatility persistence | 0.9890 | 273.66*** |
γ leverage Additional response to negative shocks | 1.0000 | 0.00 |
δ power Transformation power | 2.3474 | 2.33** |
Persistence:
1.000
Half-life:
-
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