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
Coppock Curve — a long-horizon momentum indicator: a weighted moving average of two rates of change, designed to flag major bottoms.
Quick reference
| Field | Value |
|---|---|
| Family | Price Oscillators |
| Input type | f64 (single close) |
| Output type | f64 |
| Output range | unbounded around zero |
| Default parameters | (roc_long = 14, roc_short = 11, wma_period = 10) (Python) |
| Warmup period | max(roc_long, roc_short) + wma_period |
| Interpretation | Long-term momentum; an upturn from below zero is the buy signal. |
Formula
Coppock = WMA( ROC(roc_long) + ROC(roc_short), wma_period )
Edwin Coppock built this in 1962 as a long-horizon buy signal for stock
indices. The two rates of change blend a slightly longer and a slightly
shorter momentum horizon; the Wma smooths
their sum. On a monthly chart with the conventional
(14, 11, 10) settings, the curve turning up from below zero has
historically marked the start of a new bull phase.
Parameters
| Name | Type | Default | Valid range | Description |
|---|---|---|---|---|
roc_long |
usize |
14 (Python) |
>= 1 |
Longer ROC period. 0 errors with Error::PeriodZero. |
roc_short |
usize |
11 (Python) |
>= 1 |
Shorter ROC period. |
wma_period |
usize |
10 (Python) |
>= 1 |
WMA smoothing length. |
The Python binding defaults the trio to (14, 11, 10). The periods
property returns (roc_long, roc_short, wma_period).
Inputs / Outputs
From crates/wickra-core/src/indicators/coppock.rs:
impl Indicator for Coppock {
type Input = f64;
type Output = f64;
// update(&mut self, input: f64) -> Option<f64>
}
A single f64 close in, an Option<f64> out. Python maps this to
float | None / numpy.ndarray (NaN warmup); Node to number | null /
Array<number> (NaN warmup).
Warmup
warmup_period() == max(roc_long, roc_short) + wma_period. Each ROC emits
its first value at input roc_period + 1; the longer ROC is the last to
become ready, and the WMA then needs wma_period of the summed ROC
values — so the first non-None output lands on input
max(roc_long, roc_short) + wma_period.
Edge cases
- Constant series. Both ROCs are
0on a flat series, so the WMA of zeros — and the curve — is0(constant_series_yields_zeropins this). - NaN / infinity inputs. Non-finite inputs are silently dropped; no component is advanced.
- Reset.
coppock.reset()clears both ROCs and the WMA.
Examples
Rust
use wickra::{BatchExt, Indicator, Coppock};
fn main() -> Result<(), Box<dyn std::error::Error>> {
let mut coppock = Coppock::new(14, 11, 10)?;
let prices: Vec<f64> = (1..=120).map(|i| 100.0 * 1.01_f64.powi(i)).collect();
let out = coppock.batch(&prices);
println!("warmup_period = {}", coppock.warmup_period());
println!("last > 0: {}", out.last().unwrap().unwrap() > 0.0);
Ok(())
}
Output:
warmup_period = 24
last > 0: true
A steady uptrend keeps both ROCs positive, so the Coppock Curve stays above zero.
Python
import numpy as np
import wickra as ta
coppock = ta.Coppock() # (roc_long=14, roc_short=11, wma_period=10)
prices = np.full(60, 100.0) # flat series
print(coppock.batch(prices)[-1]) # ROCs are 0 -> 0
Output:
0.0
Node
const ta = require('wickra');
const coppock = new ta.Coppock(14, 11, 10);
const prices = Array.from({ length: 120 }, (_, i) => 100 * 1.01 ** i);
console.log('warmupPeriod:', coppock.warmupPeriod());
Interpretation
Coppock is a long-horizon signal, traditionally read on monthly
data. The canonical rule is a single one: when the curve has been below
zero and turns up, that is a long-term buy. It was not designed to give
sell signals — Coppock left exits to other tools. On faster timeframes it
behaves as a smoothed momentum oscillator, but its statistical edge is
specifically the monthly bottom call.
Common pitfalls
- Using it for sell signals. The Coppock Curve is a buy-only indicator by design; pair it with a separate exit rule.
- Applying it intraday and expecting the historical edge. The documented behaviour is for monthly index charts.
References
E. S. Coppock, "Practical Relative Strength Charting", Barron's (1962).
The WMA(ROC(14) + ROC(11), 10) construction here is Coppock's original.
See also
- Indicator-Roc.md — the rate-of-change building block.
- Indicator-Wma.md — the smoothing average.
- Indicators-Overview.md — the full taxonomy.