V-Lab
Indian Rupee GARCH Volatility Analysis
High-persistence model: shocks decay very slowly, so the theoretical long-run value may not be practically meaningful
Volatility prediction for Friday, October 2nd, 2026
1 Day
2.99%
decreased by 0.10%
1 Week
3.01%
decreased by 0.08%
1 Month
3.06%
decreased by 0.03%
Analysis last updated: Thursday, October 1, 2026 at 08:52 PM UTC
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News Impact Curve
How returns affect tomorrow's volatilityVolatility Forecast
How volatility evolves over timeParameter Estimates
Jul 4, 1991 to Sep 25, 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.
σ
GARCH Model
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High persistence: persistence 1.000 ≥ 1, shocks do not decay
| Param | Value | t-stat |
|---|---|---|
| ωconst | 0.0002 | 2.38** |
| αARCH | 0.0655 | 5.92*** |
| βGARCH | 0.9345 | 94.84*** |
1.000
Persistence-
Half-lifeσ
GARCH Model
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| Parameter | Value | t-statistic |
|---|---|---|
ω const Unconditional variance weight | 0.0002 | 2.38** |
α ARCH Response to squared shocks | 0.0655 | 5.92*** |
β GARCH Volatility persistence | 0.9345 | 94.84*** |
Persistence:
1.000
Half-life:
-
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