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Miha Kralj
2026-03-13 13:47:10 -07:00
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lib/trends_FIR/rain/Rain.md
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| **Signature** | [rain_signature](rain_signature.md) |
- RAIN recursively applies SMA 10 times, producing 10 layers of progressively smoother price representation, then computes a weighted average across ...
- Parameterized by `period`.
- Output range: Tracks input.
- Requires 1 bar of warmup before first valid output (IsHot = true).
- **Similar:** [ALMA](../alma/alma.md), [FWMA](../fwma/fwma.md) | **Complementary:** ATR | **Trading note:** Raised-cosine MA; smooth taper at edges. Good sidelobe suppression for noise reduction.
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
RAIN recursively applies SMA 10 times, producing 10 layers of progressively smoother price representation, then computes a weighted average across all layers. Layers 1-4 receive weights 5, 4, 3, 2 (emphasizing the more responsive layers), while layers 5-10 each receive weight 1, for a total divisor of 20. This multi-scale composition produces a moving average that responds to short-term price changes through the lightly smoothed upper layers while maintaining stability through the heavily smoothed lower layers.
@@ -134,4 +132,4 @@ O(1) per bar. Each of the 10 SMA layers is O(1); the composite sum is 10 FMA ope
| Weighted composite | Yes | 10-element dot product; fits in 2–3 AVX2 registers |
| Cross-bar independence | Yes | Outer loop fully vectorizable: 4 output bars per pass |
Because all 10 SMA layers are independent, the entire computation can be vectorized across layers AND across bars simultaneously. AVX2 can process 4 bars per pass, each bar updating all 10 layers via 10-register prefix sums. Estimated batch speedup for large series: ~6× over scalar.
Because all 10 SMA layers are independent, the entire computation can be vectorized across layers AND across bars simultaneously. AVX2 can process 4 bars per pass, each bar updating all 10 layers via 10-register prefix sums. Estimated batch speedup for large series: ~6× over scalar.