F13c: restructure the indicator catalogue into eight families
The original taxonomy was four classical families plus a statistics group, with the F1-F12 expansion slotted in as sub-categories. This regroups the whole 71-indicator catalogue into eight top-level families, each with at least five members: Moving Averages (12), Momentum Oscillators (13), Trend & Directional (9), Price Oscillators (5), Volatility & Bands (12), Trailing Stops (5), Volume (9), Price Statistics (7). - Wiki: docs/wiki/indicators/ reorganised into eight family folders; all 71 indicator pages moved with `git mv`. Every internal cross-link is normalised to `../<family>/Indicator-X.md`, each page's `Family` field is set to its new family, and two pre-existing `../Indicator-Chaining.md` links (should have been `../../`) are corrected. A link check confirms every relative wiki link resolves. - Indicators-Overview.md fully rewritten around the eight families; Home.md indicator reference and the README family table follow suit. - Warmup-Periods.md gains the eight F13 indicators; CHANGELOG records the 46-indicator expansion (25 -> 71) and the eight-family taxonomy. - Tests: Node indicators.test.js and Python test_new_indicators.py cover all eight new indicators (Node 91/91, Python 117/117 green). cargo fmt + clippy (core/wickra/data/wasm/node) clean; 508 core tests, 25 data tests and 74 doctests green.
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# Coppock
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> Coppock Curve — a long-horizon momentum indicator: a weighted moving
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> average of two rates of change, designed to flag major bottoms.
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## Quick reference
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| Field | Value |
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|-------|-------|
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| Family | Price Oscillators |
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| Input type | `f64` (single close) |
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| Output type | `f64` |
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| Output range | unbounded around zero |
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| Default parameters | `(roc_long = 14, roc_short = 11, wma_period = 10)` (Python) |
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| Warmup period | `max(roc_long, roc_short) + wma_period` |
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| Interpretation | Long-term momentum; an upturn from below zero is the buy signal. |
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## Formula
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```
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Coppock = WMA( ROC(roc_long) + ROC(roc_short), wma_period )
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```
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Edwin Coppock built this in 1962 as a long-horizon buy signal for stock
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indices. The two rates of change blend a slightly longer and a slightly
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shorter momentum horizon; the [`Wma`](../moving-averages/Indicator-Wma.md) smooths
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their sum. On a **monthly** chart with the conventional
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`(14, 11, 10)` settings, the curve turning *up from below zero* has
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historically marked the start of a new bull phase.
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## Parameters
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| Name | Type | Default | Valid range | Description |
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|--------------|---------|---------------|-------------|-------------|
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| `roc_long` | `usize` | `14` (Python) | `>= 1` | Longer ROC period. `0` errors with `Error::PeriodZero`. |
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| `roc_short` | `usize` | `11` (Python) | `>= 1` | Shorter ROC period. |
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| `wma_period` | `usize` | `10` (Python) | `>= 1` | WMA smoothing length. |
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The Python binding defaults the trio to `(14, 11, 10)`. The `periods`
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property returns `(roc_long, roc_short, wma_period)`.
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## Inputs / Outputs
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From `crates/wickra-core/src/indicators/coppock.rs`:
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```rust
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impl Indicator for Coppock {
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type Input = f64;
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type Output = f64;
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// update(&mut self, input: f64) -> Option<f64>
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}
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```
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A single `f64` close in, an `Option<f64>` out. Python maps this to
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`float | None` / `numpy.ndarray` (NaN warmup); Node to `number | null` /
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`Array<number>` (NaN warmup).
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## Warmup
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`warmup_period() == max(roc_long, roc_short) + wma_period`. Each ROC emits
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its first value at input `roc_period + 1`; the longer ROC is the last to
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become ready, and the WMA then needs `wma_period` of the summed ROC
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values — so the first non-`None` output lands on input
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`max(roc_long, roc_short) + wma_period`.
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## Edge cases
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- **Constant series.** Both ROCs are `0` on a flat series, so the WMA of
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zeros — and the curve — is `0` (`constant_series_yields_zero` pins
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this).
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- **NaN / infinity inputs.** Non-finite inputs are silently dropped; no
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component is advanced.
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- **Reset.** `coppock.reset()` clears both ROCs and the WMA.
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## Examples
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### Rust
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```rust
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use wickra::{BatchExt, Indicator, Coppock};
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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let mut coppock = Coppock::new(14, 11, 10)?;
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let prices: Vec<f64> = (1..=120).map(|i| 100.0 * 1.01_f64.powi(i)).collect();
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let out = coppock.batch(&prices);
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println!("warmup_period = {}", coppock.warmup_period());
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println!("last > 0: {}", out.last().unwrap().unwrap() > 0.0);
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Ok(())
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}
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```
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Output:
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```
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warmup_period = 24
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last > 0: true
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```
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A steady uptrend keeps both ROCs positive, so the Coppock Curve stays
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above zero.
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### Python
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```python
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import numpy as np
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import wickra as ta
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coppock = ta.Coppock() # (roc_long=14, roc_short=11, wma_period=10)
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prices = np.full(60, 100.0) # flat series
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print(coppock.batch(prices)[-1]) # ROCs are 0 -> 0
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```
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Output:
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```
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0.0
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```
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### Node
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```javascript
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const ta = require('wickra');
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const coppock = new ta.Coppock(14, 11, 10);
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const prices = Array.from({ length: 120 }, (_, i) => 100 * 1.01 ** i);
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console.log('warmupPeriod:', coppock.warmupPeriod());
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```
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## Interpretation
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`Coppock` is a long-horizon signal, traditionally read on **monthly**
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data. The canonical rule is a single one: when the curve has been below
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zero and turns up, that is a long-term buy. It was not designed to give
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sell signals — Coppock left exits to other tools. On faster timeframes it
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behaves as a smoothed momentum oscillator, but its statistical edge is
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specifically the monthly bottom call.
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## Common pitfalls
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- **Using it for sell signals.** The Coppock Curve is a buy-only
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indicator by design; pair it with a separate exit rule.
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- **Applying it intraday and expecting the historical edge.** The
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documented behaviour is for monthly index charts.
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## References
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E. S. Coppock, "Practical Relative Strength Charting", *Barron's* (1962).
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The `WMA(ROC(14) + ROC(11), 10)` construction here is Coppock's original.
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## See also
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- [Indicator-Roc.md](../momentum-oscillators/Indicator-Roc.md) — the rate-of-change building block.
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- [Indicator-Wma.md](../moving-averages/Indicator-Wma.md) — the smoothing average.
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- [Indicators-Overview.md](../../Indicators-Overview.md) — the full taxonomy.
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