AwesomeOscillator

Bill Williams' Awesome Oscillator — the difference of two simple moving averages computed on the bar's median price (high + low) / 2.

Quick reference

Field	Value
Family	Momentum Oscillators
Input type	Candle
Output type	f64
Output range	unbounded (centred on 0; in price-difference units)
Default parameters	fast = 5, slow = 34 (AwesomeOscillator::classic(), Python default)
Warmup period	slow_period (34 for the classic configuration)
Interpretation	zero-line cross; "saucer" and "twin-peaks" Bill Williams patterns

Formula

For each new candle, compute the median price:

median_t  =  (high_t + low_t) / 2

Then AO is the difference of two SMAs of that series:

AO_t  =  SMA_fast(median)_t  −  SMA_slow(median)_t

There is no smoothing on top — the output is in the same units as the input prices (a number, not a percent).

Parameters

Name	Type	Default (Python)	Valid range	Description
fast	usize	5	>= 1 and < slow	Fast SMA period over median price.
slow	usize	34	>= 1 and > fast	Slow SMA period over median price.

AwesomeOscillator::new returns Error::PeriodZero if either period is zero and Error::InvalidPeriod if fast >= slow.

Inputs / Outputs

From impl Indicator for AwesomeOscillator:

use wickra::{Indicator, AwesomeOscillator, Candle};
// AwesomeOscillator: Input = Candle, Output = f64
const _: fn(&mut AwesomeOscillator, Candle) -> Option<f64> = <AwesomeOscillator as Indicator>::update;

The close and volume fields on the input candle are ignored — only high and low matter, via Candle::median_price().

Python's AwesomeOscillator.batch(high, low) returns a 1-D float64array.array('d'). Node's AwesomeOscillator.batch(high, low) returns a flat number[]. Both produce NaN during warmup; only Python exposes a streaming update(candle) method.

Warmup

warmup_period() returns slow_period. The slow SMA is the slower of the two SMAs, and because both consume the same median-price stream the first time both have valid output is exactly the slow_period-th input. For the classic (5, 34) configuration this is 34 — verified above.

Edge cases

• Constant input. Both SMAs converge to the constant median price, so AO == 0 (test constant_series_yields_zero).
• Reset. reset() resets both SMAs; the next slow_period updates return None.

Examples

Rust

use wickra::{AwesomeOscillator, BatchExt, Candle, Indicator};

let candles: Vec<Candle> = (0..40)
    .map(|i| {
        let m = 100.0 + i as f64;
        Candle::new(m, m + 1.0, m - 1.0, m, 1.0, 0).unwrap()
    })
    .collect();
let mut ao = AwesomeOscillator::classic();
let out = ao.batch(&candles);
println!("row 33 = {}", out[33].unwrap());
println!("row 39 = {}", out[39].unwrap());

Verified output:

row 33 = 14.5
row 39 = 14.5

(SMA(5) − SMA(34) on a unit-slope ramp converges to a constant offset that depends only on the difference between the two windows' centres, which is why both rows print the same number.)

Python

import numpy as np
import wickra as ta

n = 40
i = np.arange(n, dtype=float)
m = 100.0 + i
high = m + 1.0
low  = m - 1.0
ao = ta.AwesomeOscillator(5, 34)
out = ao.batch(high, low)
print('warmup:', ao.warmup_period())
print('row 33:', out[33])
print('row 39:', out[39])

Verified output:

warmup: 34
row 33: 14.5
row 39: 14.5

Node

const wickra = require('wickra');

const n = 40;
const high = [], low = [];
for (let i = 0; i < n; i++) {
  const m = 100 + i;
  high.push(m + 1);
  low.push(m - 1);
}
const ao = new wickra.AwesomeOscillator(5, 34);
const out = ao.batch(high, low);
console.log('row 33:', out[33]);
console.log('row 39:', out[39]);

Verified output:

row 33: 14.5
row 39: 14.5

Interpretation

• Zero-line cross. AO crossing zero from below is a bullish momentum signal — the fast SMA of median price has overtaken the slow SMA. The mirror cross is bearish.
• Saucer. A short sequence of bars where AO turns from negative to positive momentum without crossing zero (two declining-magnitude bars on the same side of zero followed by a turn) is Bill Williams' "saucer" pattern.
• Twin peaks. Two AO peaks on the same side of the zero line, with the second peak lower (or shallower) than the first while price pushes further, is Williams' divergence-style "twin peaks" pattern.

Common pitfalls

• Median-price input, not close. AO ignores close entirely. If your data source reports an "average" price or only closes, you must reconstruct high and low or pick a different oscillator (e.g. MACD on closes).
• Output magnitude depends on the asset. Because AO is in raw price units, an AO of 14.5 on a price ramp through 100..140 means something completely different than 14.5 on a price stream near 0.00012. Always interpret AO relative to a per-asset baseline or normalise by ATR.

References

• Bill Williams, Trading Chaos: Applying Expert Techniques to Maximize Your Profits, Wiley, 1995 — introduces the Awesome Oscillator alongside the rest of the Profitunity tool set.

See also

• Indicator: MacdIndicator — sister oscillator on closes (with an extra signal line on top).
• Indicator: Trix — momentum oscillator on a triple-smoothed series.
• Warmup Periods — bare slow_period.