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.
245 lines
7.8 KiB
Markdown
245 lines
7.8 KiB
Markdown
# ADX
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> Wilder's Average Directional Index — the smoothed strength of a trend,
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> plus the two directional components (`+DI`, `−DI`) that say which
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> direction the trend is going.
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## Quick reference
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| Field | Value |
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|-------|-------|
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| Family | Trend & Directional |
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| Input type | `Candle` |
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| Output type | `AdxOutput { plus_di, minus_di, adx }` |
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| Output range | each field in `[0, 100]` |
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| Default parameters | `period = 14` (Python) |
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| Warmup period | `2 · period` (28 for `period = 14`) |
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| Interpretation | `adx > 25` means a meaningful trend; the dominant DI gives its direction |
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## Formula
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For each new candle at time `t` (with previous candle `t-1`):
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```
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+DM_t = high_t − high_{t-1} if (high_t − high_{t-1}) > (low_{t-1} − low_t)
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and (high_t − high_{t-1}) > 0
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= 0 otherwise
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−DM_t = low_{t-1} − low_t if (low_{t-1} − low_t) > (high_t − high_{t-1})
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and (low_{t-1} − low_t) > 0
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= 0 otherwise
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TR_t = max(high_t − low_t,
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|high_t − close_{t-1}|,
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|low_t − close_{t-1}|)
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```
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Wilder's smoothing is applied to all three series. Seeding is a simple
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sum over the first `period` post-prev candles; after seeding the update
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rule for any of these is
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```
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S_t = S_{t-1} − S_{t-1} / period + X_t
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```
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where `X_t` is `TR_t`, `+DM_t`, or `−DM_t`. The directional indicators
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and DX then are
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```
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+DI_t = 100 · (+DM smoothed)_t / (TR smoothed)_t
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−DI_t = 100 · (−DM smoothed)_t / (TR smoothed)_t
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DX_t = 100 · |+DI_t − −DI_t| / (+DI_t + −DI_t)
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```
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`ADX_t` is itself a Wilder-smoothed `DX` series, seeded as the mean of
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the first `period` `DX` values, and then updated with `α = 1/period`:
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```
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ADX_t = (ADX_{t-1} · (period − 1) + DX_t) / period
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```
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When `+DI + −DI == 0`, `DX` is `0`; when `TR == 0`, both DI lines are
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`0`. These are the divide-by-zero guards in `Adx::update`.
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## Parameters
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| Name | Type | Default (Python) | Valid range | Description |
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|------|------|------------------|-------------|-------------|
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| `period` | `usize` | `14` | `>= 1` | Wilder smoothing length shared by `+DM`, `−DM`, `TR`, and `ADX`. |
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`Adx::new(0)` returns `Error::PeriodZero`.
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## Inputs / Outputs
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From `impl Indicator for Adx`:
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```rust
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type Input = Candle;
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type Output = AdxOutput;
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fn update(&mut self, candle: Candle) -> Option<AdxOutput>;
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```
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`AdxOutput`:
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| Field | Description |
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|-------|-------------|
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| `plus_di` | Plus Directional Indicator (`+DI`) — strength of upward movement. |
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| `minus_di` | Minus Directional Indicator (`−DI`) — strength of downward movement. |
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| `adx` | Average Directional Index — smoothed `|DX|`, a directionless trend-strength measure. |
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Python's `ADX.batch(high, low, close)` returns a `(n, 3)` `float64` array
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with columns `[plus_di, minus_di, adx]`; warmup rows are entirely `NaN`.
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The streaming `update(candle)` returns a `(plus_di, minus_di, adx)`
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tuple or `None`.
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Node's `ADX.batch(high, low, close)` returns a flat `number[]` of length
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`n * 3`, interleaved `[plus_di_0, minus_di_0, adx_0, plus_di_1, …]`.
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Only `batch` is exposed on the Node binding — no `update`.
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## Warmup
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`warmup_period()` returns `2 · period`. The first candle just provides a
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"previous" reference (no DM/TR can be computed yet); the next `period`
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candles seed the smoothed `+DM`, `−DM`, and `TR` sums; the next `period`
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candles after that produce `DX` values that seed `ADX`. For `period =
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14` that's `1 + 14 + 13 = 28` candles before the first full
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`AdxOutput`, which matches `2 · 14 = 28`.
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## Edge cases
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- **Strong unidirectional trend.** If every candle is strictly higher
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than the last (with `+DM` always positive, `−DM` always zero), `+DI`
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saturates at `100`, `−DI` at `0`, and `ADX` climbs toward `100`. The
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example below produces exactly that.
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- **Flat market (no high/low movement).** Every `TR`, `+DM`, `−DM` is
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zero, so the divide-by-zero guards return `+DI = −DI = 0` and `DX =
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0`; `ADX` then sits at `0` indefinitely.
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- **Reset.** `reset()` clears `prev`, all seed sums and counts, all
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smoothed values, the DX buffer, and `adx_value`.
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## Examples
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### Rust
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```rust
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use wickra::{Adx, BatchExt, Candle, Indicator};
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let candles: Vec<Candle> = (0..40)
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.map(|i| {
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let base = 100.0 + i as f64 * 2.0;
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Candle::new(base + 0.5, base + 1.0, base - 0.5, base + 0.5, 1.0, 0).unwrap()
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})
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.collect();
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let mut adx = Adx::new(14)?;
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let out = adx.batch(&candles);
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let v = out[27].unwrap();
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println!("row 27 +DI={} -DI={} ADX={}", v.plus_di, v.minus_di, v.adx);
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let v = out[39].unwrap();
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println!("row 39 +DI={} -DI={} ADX={}", v.plus_di, v.minus_di, v.adx);
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# Ok::<(), wickra::Error>(())
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```
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Verified output:
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```
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row 27 +DI=80 -DI=0 ADX=100
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row 39 +DI=80 -DI=0 ADX=100
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```
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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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n = 40
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i = np.arange(n, dtype=float)
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base = 100.0 + i * 2.0
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high = base + 1.0
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low = base - 0.5
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close = base + 0.5
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adx = ta.ADX(14)
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out = adx.batch(high, low, close)
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print('warmup:', adx.warmup_period())
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print('shape :', out.shape)
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print('row 27:', out[27])
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print('row 39:', out[39])
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```
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Verified output:
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```
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warmup: 28
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shape : (40, 3)
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row 27: [ 80. 0. 100.]
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row 39: [ 80. 0. 100.]
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```
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### Node
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```javascript
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const wickra = require('wickra');
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const n = 40;
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const high = [], low = [], close = [];
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for (let i = 0; i < n; i++) {
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const b = 100 + i * 2;
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high.push(b + 1);
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low.push(b - 0.5);
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close.push(b + 0.5);
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}
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const adx = new wickra.ADX(14);
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const out = adx.batch(high, low, close);
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console.log('len :', out.length);
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console.log('row 27:', { plusDi: out[27 * 3], minusDi: out[27 * 3 + 1], adx: out[27 * 3 + 2] });
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console.log('row 39:', { plusDi: out[39 * 3], minusDi: out[39 * 3 + 1], adx: out[39 * 3 + 2] });
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```
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Verified output:
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```
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len : 120
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row 27: { plusDi: 80, minusDi: 0, adx: 100 }
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row 39: { plusDi: 80, minusDi: 0, adx: 100 }
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```
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## Interpretation
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- **Trend-strength bands.** `ADX < 20` is typically read as a ranging
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market; `ADX > 25` as a "real" trend; `ADX > 40` as a strong trend.
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ADX itself is direction-agnostic — you need `+DI` vs `−DI` to know
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which way the trend points.
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- **DI crossover.** `+DI` crossing above `−DI` is a bullish directional
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signal; the mirror is bearish. Many traders only act on a crossover
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when `ADX > 25` to filter out crossovers in a ranging market.
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- **ADX peaks.** A rising ADX confirms trend continuation; a falling
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ADX from a high level suggests the current trend is exhausting (even
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if `+DI` still dominates `−DI`).
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## Common pitfalls
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- **Long warmup.** ADX needs `2 · period` candles before the first
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emission — twice as many as most other Wilder indicators. A common
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bug is reusing an "RSI fits in `period + 1` bars" mental model and
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reading garbage during the ADX warmup; check `is_ready()` or test
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for `NaN` on the `adx` column.
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- **Plotted on the same axis as DI.** `+DI`, `−DI`, and `ADX` all live
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in `[0, 100]` and are typically overlaid. The crossover signal is
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between `+DI` and `−DI` only — `ADX` does not cross either of them
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for any directional meaning.
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## References
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- J. Welles Wilder, *New Concepts in Technical Trading Systems*, Trend
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Research, 1978 — the original publication of `+DI`, `−DI`, `DX`,
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`ADX`, and the smoothing scheme they share with RSI and ATR.
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## See also
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- [Indicator: Rsi](../momentum-oscillators/Indicator-Rsi.md) — shares Wilder smoothing.
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- [Indicator: Aroon](../trend-directional/Indicator-Aroon.md) — alternative trend-strength
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measure, range-based.
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- [Indicator: MacdIndicator](../trend-directional/Indicator-MacdIndicator.md) — trend-following
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momentum, useful as a confirmation against `+DI` / `−DI`.
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- [Warmup Periods](../../Warmup-Periods.md) — the `2 · period` ADX entry.
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