# UltimateOscillator > Ultimate Oscillator — Larry Williams' momentum oscillator that blends > three lookback periods into one bounded `[0, 100]` reading. ## Quick reference | Field | Value | |-------|-------| | Family | Momentum Oscillators | | Input type | `Candle` (uses `high`, `low`, `close`) | | Output type | `f64` | | Output range | `[0, 100]` | | Default parameters | `(short = 7, mid = 14, long = 28)` (Python) | | Warmup period | `max(short, mid, long) + 1` | | Interpretation | Weighted three-timeframe buying pressure; `50` is neutral. | ## Formula ``` true_low_t = min(low_t, close_{t−1}) BP_t = close_t − true_low_t (buying pressure) TR_t = max(high_t, close_{t−1}) − true_low_t (true range) avg_n = Σ BP over n / Σ TR over n UO = 100 · (4·avg_short + 2·avg_mid + avg_long) / 7 ``` A single-timeframe momentum oscillator can show false divergences when its lookback does not match the swing being measured. The Ultimate Oscillator averages buying pressure over *three* windows and weights the fastest (`4×`) above the medium (`2×`) and slow (`1×`), which damps those false signals while keeping the response quick. ## Parameters | Name | Type | Default | Valid range | Description | |---------|---------|---------------|-------------|-------------| | `short` | `usize` | `7` (Python) | `>= 1` | Fast lookback (weight `4`). `0` errors with `Error::PeriodZero`. | | `mid` | `usize` | `14` (Python) | `>= 1` | Medium lookback (weight `2`). | | `long` | `usize` | `28` (Python) | `>= 1` | Slow lookback (weight `1`). | The Python binding defaults the trio to `(7, 14, 28)` via `#[pyo3(signature = (short=7, mid=14, long=28))]`. Node and WASM take all three explicitly. The `periods` property returns `(short, mid, long)`. `UltimateOscillator::classic()` is the conventional `(7, 14, 28)`. ## Inputs / Outputs From `crates/wickra-core/src/indicators/ultimate_oscillator.rs`: ```rust impl Indicator for UltimateOscillator { type Input = Candle; type Output = f64; // update(&mut self, input: Candle) -> Option } ``` `UltimateOscillator` is a **candle-input** indicator: it reads `high`, `low` and `close`. In Python the streaming `update` accepts a 6-tuple or a dict; the batch helper takes `high`, `low`, `close` numpy arrays. Node and WASM expose `update(high, low, close)` and `batch(high, low, close)`. ## Warmup `warmup_period() == max(short, mid, long) + 1`. The first bar has no previous close, so the first `BP`/`TR` pair forms on bar 2; the longest window must then fill, so the first non-`None` output lands on input `max(short, mid, long) + 1`. ## Edge cases - **Pure uptrend.** Bars that each close higher have `BP == TR`, so every ratio is `1` and UO saturates at `100` (`pure_uptrend_saturates_at_100` pins this). - **Pure downtrend.** Bars that each close lower have `BP == 0`, so UO is `0` (`pure_downtrend_saturates_at_0` pins this). - **Flat market.** Identical bars have zero true range; each window contributes the neutral ratio `0.5`, so UO reads `50` (`flat_market_reads_50` pins this). - **Bounds.** The output is always within `[0, 100]` (`output_stays_within_0_100` pins this). - **Candle validation.** `Candle::new` rejects NaN/infinite fields, so `update` never sees an invalid bar. - **Reset.** `uo.reset()` clears the previous close, the rolling window and all six running sums. ## Examples ### Rust ```rust use wickra::{BatchExt, Candle, Indicator, UltimateOscillator}; fn main() -> Result<(), Box> { let mut uo = UltimateOscillator::classic(); // (7, 14, 28) // 30 flat candles, each closing one tick higher than the last. let candles: Vec = (0..40) .map(|i| { let p = 100.0 + f64::from(i); Candle::new(p, p, p, p, 1.0, i64::from(i)).unwrap() }) .collect(); let out = uo.batch(&candles); println!("warmup_period = {}", uo.warmup_period()); println!("last = {:?}", out.last().unwrap()); Ok(()) } ``` Output: ``` warmup_period = 29 last = Some(100.0) ``` Every bar closes higher with `BP == TR`, so UO saturates at `100`. This matches the `pure_uptrend_saturates_at_100` test in `crates/wickra-core/src/indicators/ultimate_oscillator.rs`. ### Python ```python import numpy as np import wickra as ta uo = ta.UltimateOscillator() # (7, 14, 28) high = np.full(40, 100.0) low = np.full(40, 100.0) close = np.full(40, 100.0) # perfectly flat market print(uo.batch(high, low, close)[-1]) ``` Output: ``` 50.0 ``` ### Node ```javascript const ta = require('wickra'); const uo = new ta.UltimateOscillator(7, 14, 28); const flat = Array.from({ length: 40 }, () => 100); console.log(uo.batch(flat, flat, flat).at(-1)); // 50 ``` ## Interpretation `UltimateOscillator` is read with the usual overbought/oversold lens — above `70` is stretched, below `30` is washed out — but Larry Williams' canonical signal is *divergence with confirmation*: price makes a new extreme while UO does not, then UO breaks the level of the divergence. The three-timeframe blend makes those divergences more reliable than a single-period oscillator. ## Common pitfalls - **Feeding it scalar prices.** It needs `high`/`low`/`close`; it takes a `Candle`, not an `f64`. - **Reordering the periods.** The `4 / 2 / 1` weights assume `short` is the fastest window — keep `short < mid < long`. Any positive periods are accepted, but mis-ordering them inverts the intended weighting. ## References Larry Williams, "The Ultimate Oscillator", *Technical Analysis of Stocks & Commodities* (1985). The buying-pressure / true-range definition and the `4 / 2 / 1` weighting follow Williams' original. ## See also - [Indicator-Stochastic.md](../momentum-oscillators/Indicator-Stochastic.md) — single-timeframe bounded oscillator. - [Indicator-Rsi.md](../momentum-oscillators/Indicator-Rsi.md) — the canonical momentum oscillator. - [Indicators-Overview.md](../../Indicators-Overview.md) — the full taxonomy.