V-Lab
Securitize Corp APARCH Volatility Analysis
High-persistence model: shocks decay very slowly, so the theoretical long-run value may not be practically meaningful
Volatility prediction for Wednesday, September 16th, 2026
1 Day
84.40%
1 Week
85.43%
1 Month
89.49%
Analysis last updated: Tuesday, September 15, 2026 at 09:36 PM UTC
News Impact Curve
How returns affect tomorrow's volatilityVolatility Forecast
How volatility evolves over timeParameter Estimates
May 2, 2025 to Sep 11, 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 = 1.66 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 | 0.1624 | 1.06 |
| αARCH | 0.2014 | 1.83* |
| βGARCH | 0.7986 | 9.69*** |
| γleverage | -0.4601 | -1.17 |
| δpower | 1.6584 | 1.57 |
1.000
Persistence-
Half-lifeAPARCH Model
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| Parameter | Value | t-statistic |
|---|---|---|
ω const Unconditional variance weight | 0.1624 | 1.06 |
α ARCH Response to squared shocks | 0.2014 | 1.83* |
β GARCH Volatility persistence | 0.7986 | 9.69*** |
γ leverage Additional response to negative shocks | -0.4601 | -1.17 |
δ power Transformation power | 1.6584 | 1.57 |
Persistence:
1.000
Half-life:
-
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