kingchenc
7728151c87
Completes the F3 family (Momentum) end to end: - Rust core: mom.rs (raw price-difference momentum), cmo.rs (Chande Momentum Oscillator — unsmoothed gain/loss sum, bounded [-100,100]), tsi.rs (True Strength Index — double-EMA-smoothed momentum ratio), pmo.rs (DecisionPoint Price Momentum Oscillator — doubly-smoothed ROC with the 2/period custom smoothing). Each with a full Indicator impl, runnable doctest and reference-value / saturation / warmup / reset / batch==streaming / non-finite tests. - Python: PyMom / PyCmo / PyTsi / PyPmo PyO3 classes + module registration + .pyi stubs (defaults MOM=10, CMO=14, TSI=(25,13), PMO=(35,20)). - Node: MomNode / CmoNode via the scalar macro, explicit TsiNode and PmoNode; index.d.ts and index.js updated. - WASM: WasmMom / WasmCmo / WasmTsi / WasmPmo via the scalar macro. - Wiki: Indicator-Mom/Cmo/Tsi/Pmo.md plus rows in Indicators-Overview.md and entries in Home.md. cargo fmt + clippy (core/wickra/data/wasm/node) clean; 262 core tests, 25 data tests and 37 doctests green.
157 lines
4.3 KiB
Markdown
157 lines
4.3 KiB
Markdown
# CMO
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> Chande Momentum Oscillator — a bounded `[−100, 100]` momentum gauge from
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> the unsmoothed sum of gains versus losses.
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## Quick reference
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| Field | Value |
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|-------|-------|
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| Family | Momentum |
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| Sub-category | Bounded oscillators (−100 … 100) |
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| Input type | `f64` (single close) |
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| Output type | `f64` |
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| Output range | `[−100, 100]` |
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| Default parameters | `period = 14` (Python) |
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| Warmup period | `period + 1` |
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| Interpretation | `+100` pure gains, `−100` pure losses, `0` balanced. |
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## Formula
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Over the last `period` price *changes*, sum the gains and the losses
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separately:
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```
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gain_t = max(price_t − price_{t−1}, 0)
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loss_t = max(price_{t−1} − price_t, 0)
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CMO = 100 · (Σ gain − Σ loss) / (Σ gain + Σ loss)
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```
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Unlike RSI — which Wilder-smooths the gain/loss averages — CMO sums them
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raw, with equal weight on every change in the window. That makes it
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faster and wider-swinging than RSI at the same period.
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## Parameters
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| Name | Type | Default | Valid range | Description |
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|----------|---------|---------------|-------------|-------------|
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| `period` | `usize` | `14` (Python) | `>= 1` | Number of price changes summed. `period = 0` errors with `Error::PeriodZero`. |
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The Python binding defaults `period` to `14` via `#[pyo3(signature = (period=14))]`.
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## Inputs / Outputs
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From `crates/wickra-core/src/indicators/cmo.rs`:
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```rust
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impl Indicator for Cmo {
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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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`Cmo::new(period).warmup_period() == period + 1`. The first price change
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needs two inputs, and the gain/loss window must hold `period` changes, so
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the first non-`None` output lands on input `period + 1`.
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## Edge cases
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- **Pure trend.** A window of only gains returns `+100`; only losses,
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`−100` (`pure_uptrend_saturates_at_plus_100` /
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`pure_downtrend_saturates_at_minus_100` pin this).
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- **Constant series.** A flat series has no gains and no losses; the
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`0 / 0` is guarded and the output is `0.0`
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(`constant_series_yields_zero` pins this).
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- **NaN / infinity inputs.** Non-finite inputs are silently dropped; state
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is left untouched.
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- **Reset.** `cmo.reset()` clears the previous price, the gain/loss window
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and both running sums.
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## Examples
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### Rust
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```rust
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use wickra::{BatchExt, Indicator, Cmo};
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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let mut cmo = Cmo::new(3)?;
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let out: Vec<Option<f64>> = cmo.batch(&[10.0, 11.0, 10.0, 12.0]);
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println!("{:?}", out);
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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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[None, None, None, Some(50.0)]
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```
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The three changes are `+1, −1, +2`: `Σ gain = 3`, `Σ loss = 1`, so
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`CMO = 100·(3 − 1)/(3 + 1) = 50`. This matches the `reference_value` test
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in `crates/wickra-core/src/indicators/cmo.rs`.
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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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cmo = ta.CMO(3)
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print(cmo.batch(np.array([10.0, 11.0, 10.0, 12.0])))
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```
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Output:
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```
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[nan nan nan 50.]
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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 cmo = new ta.CMO(3);
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console.log(cmo.batch([10, 11, 10, 12]));
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```
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Output:
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```
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[ NaN, NaN, NaN, 50 ]
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```
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## Interpretation
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`Cmo` is read like other bounded oscillators: readings near `+50` and
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above flag overbought conditions, near `−50` and below oversold, and the
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zero line marks the gain/loss balance point. Because it is unsmoothed it
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reacts a bar or two sooner than RSI but is noisier — pair it with a slower
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filter, or use it for divergence rather than raw threshold triggers.
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## Common pitfalls
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- **Expecting the `[0, 100]` RSI scale.** `Cmo` is centred on zero and
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spans `[−100, 100]`; an RSI of `30` corresponds to a `Cmo` near `−40`.
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- **Treating it as a smoothed average.** `Cmo` sums raw changes — it is
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deliberately not Wilder-smoothed.
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## References
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Tushar Chande, *The New Technical Trader* (1994). The unsmoothed
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gain/loss sum here matches the original definition and TA-Lib's `CMO`.
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## See also
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- [Indicator-Rsi.md](Indicator-Rsi.md) — the Wilder-smoothed relative.
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- [Indicator-Mom.md](Indicator-Mom.md) — raw price-difference momentum.
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- [Indicators-Overview.md](../../Indicators-Overview.md) — the full taxonomy.
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