Chinese Renminbi 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, July 22nd, 2026
1 Day
1.51%
1 Week
1.52%
1 Month
1.53%
Analysis last updated: Tuesday, July 21, 2026 at 07:19 PM UTC
News Impact Curve
How returns affect tomorrow's volatilityVolatility Forecast
How volatility evolves over timeParameter Estimates
Jul 29, 2005 to Jul 17, 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 = 2.19 sits above 2, so large shocks influence volatility more than quadratically, dominating the response more than in standard GARCH.
Inverse leverage: Positive returns increase volatility 27% more than negative returns
APARCH Model
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| Parameter | Value | t-statistic |
|---|---|---|
ω const Unconditional variance weight | 0.0000 | 2.50** |
α ARCH Response to squared shocks | 0.0343 | 16.78*** |
β GARCH Volatility persistence | 0.9630 | 741.89*** |
γ leverage Additional response to negative shocks | -0.0540 | -3.44*** |
δ power Transformation power | 2.1910 | 23.26*** |
Persistence:
1.000
Half-life:
-
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