Indian Rupee 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, October 14th, 2026
1 Day
6.87%
1 Week
6.88%
1 Month
6.90%
Analysis last updated: Tuesday, October 13, 2026 at 07:11 PM UTC
News Impact Curve
How returns affect tomorrow's volatilityVolatility Forecast
How volatility evolves over timeParameter Estimates
Jul 4, 1991 to Oct 9, 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.
Inverse leverage: Positive returns increase volatility 109% more than negative returns
APARCH Model
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| Param | Value | t-stat |
|---|---|---|
| ωconst | 0.0002 | 1.10 |
| αARCH | 0.0621 | 4.79*** |
| βGARCH | 0.9379 | 115.91*** |
| γleverage | -0.1910 | -2.77*** |
| δpower | 1.9117 | 8.44*** |
1.000
Persistence-
Half-lifeAPARCH Model
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| Parameter | Value | t-statistic |
|---|---|---|
ω const Unconditional variance weight | 0.0002 | 1.10 |
α ARCH Response to squared shocks | 0.0621 | 4.79*** |
β GARCH Volatility persistence | 0.9379 | 115.91*** |
γ leverage Additional response to negative shocks | -0.1910 | -2.77*** |
δ power Transformation power | 1.9117 | 8.44*** |
Persistence:
1.000
Half-life:
-
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