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Enhance documentation and validation for various indicators

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Miha Kralj
2025-12-22 20:42:26 -08:00
parent 5bb8c122c0
commit 4efa0e773e
81 changed files with 4267 additions and 640 deletions
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lib/trends/pwma/Pwma.md
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@@ -28,7 +28,8 @@ Despite the "parabolic" name, the performance is linear O(1) per update.
| Metric | Score | Notes |
| :--- | :--- | :--- |
| **Throughput** | High | Triple running sum O(1) |
| **Throughput** | [N] ns/bar | Triple running sum O(1) |
| **Allocations** | 0 | Stack-based calculations only |
| **Complexity** | O(1) | Constant time update |
| **Accuracy** | 8/10 | Heavily weighted to most recent price |
| **Timeliness** | 9/10 | Very fast reaction to new data |
@@ -37,12 +38,16 @@ Despite the "parabolic" name, the performance is linear O(1) per update.
## Validation
Validated against brute-force calculation (sum of products).
Validated against Ooples.
| Provider | Error Tolerance | Notes |
| Library | Status | Notes |
| :--- | :--- | :--- |
| **Manual Calc** | $10^{-9}$ | Verified against O(N) implementation |
| **QuanTAlib** | ✅ | Validated. |
| **Ooples** | ✅ | Matches `CalculateParabolicWeightedMovingAverage` |
| **Skender** | N/A | Not implemented |
| **TA-Lib** | N/A | Not implemented |
| **Tulip** | N/A | Not implemented. |
### Common Pitfalls
1. **Resync**: Because triple running sums are used, floating-point errors can accumulate faster than in a simple SMA. The implementation automatically resyncs every 1000 ticks to maintain precision.