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lib/trends_FIR/fwma/Fwma.md

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 # FWMA: Fibonacci Weighted Moving Average
 
+| Property         | Value                            |
+| ---------------- | -------------------------------- |
+| **Category**     | Trend (FIR MA)                        |
+| **Inputs**       | Source (close)                          |
+| **Parameters**   | `period` (default 10)                      |
+| **Outputs**      | Single series (Fwma)                       |
+| **Output range** | Tracks input                     |
+| **Warmup**       | `period` bars                          |
+
+### TL;DR
+
+- The Fibonacci Weighted Moving Average applies the Fibonacci sequence as FIR filter weights, assigning exponentially growing importance to recent bars.
+- Parameterized by `period` (default 10).
+- Output range: Tracks input.
+- Requires `period` bars of warmup before first valid output (IsHot = true).
+- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
+
 > "Nature uses Fibonacci for sunflower seeds and nautilus shells. Using it for price weighting is either profound biological insight or the most expensive numerology in finance. The math doesn't care which."
 
 The Fibonacci Weighted Moving Average applies the Fibonacci sequence as FIR filter weights, assigning exponentially growing importance to recent bars. Where WMA uses linear weights (1, 2, 3, ..., N) and PWMA uses parabolic weights ($1^2, 2^2, ..., N^2$), FWMA uses F(1), F(2), ..., F(N). The Fibonacci growth rate ($\phi \approx 1.618$) produces a weighting profile between exponential and parabolic, giving FWMA a distinctive "golden ratio decay" that concentrates roughly 61.8% of total weight in the most recent third of the window.