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Stochastic Oscillator

Classic momentum oscillator overbought oversold classic

A momentum indicator comparing a particular closing price of a security to a range of its prices over a certain period of time.

Visual Example

Stochastic Oscillator — annotated preview mapping to core implementation

Synthetic ideal per library logic. Generated 2026-06-25 IST via docs/generate_all_previews.py (reproducible; maps to core Next<T> implementation).

Description

The Stochastic Oscillator indicator is a technical analysis tool that a momentum indicator comparing a particular closing price of a security to a range of its prices over a certain period of time.

This indicator is primarily used for identifying key market conditions. It provides a robust signal that can be easily integrated into both simple strategies and more complex machine learning feature pipelines. Compared to its alternatives, it offers a distinct balance of responsiveness and stability.

Traders often combine this with other metrics to confirm signals and avoid false positives during sideways market regimes. It remains a standard tool for systematic trading models.

Use to identify trend reversals by looking for crossovers and overbought/oversold levels. The %K and %D lines indicate when the momentum is shifting relative to the recent price range.

George Lane developed the Stochastic Oscillator in the 1950s. It is based on the observation that in an uptrend, prices tend to close near their high, and in a downtrend, they tend to close near their low. The sensitivity of the oscillator to market movements is reducible by adjusting the time period or by taking a moving average of the result. — StockCharts ChartSchool

QuantWave implements this indicator via the universal Next<T> trait, guaranteeing bit-identical results between Rust streaming, Python streaming, and Polars batch (.ta() / map_batches) surfaces.

Formula / Specification

Implementation (quantwave-core/src/indicators/momentum.rs):

\[ \%K = 100 \times \frac{C - L14}{H14 - L14} \\ \%D = 3\text{-period SMA of } \%K \]

Gold-standard parity vectors: quantwave-core/tests/gold_standard/stoch.json.

Parameters

Parameter Default Description
fastk_period 5 Fast %K period
slowk_period 3 Slow %K period
slowd_period 3 Slow %D period

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::STOCH;
use quantwave_core::traits::Next;

let mut ind = STOCH::new(5);
for price in &prices {
    let value = ind.next(price);
}

Streaming (Python)

from quantwave import STOCH

ind = STOCH(5)
for price in prices:
    value = ind.next(price)

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_stochastic_oscillator(series: pl.Series) -> pl.Series:
    ind = qw.STOCH(5)
    return pl.Series([ind.next(float(v)) for v in series.to_list()])

df = (
    pl.read_csv('ohlcv.csv')
    .lazy()
    .with_columns(
        pl.col("close").map_batches(apply_stochastic_oscillator, return_dtype=pl.Float64).alias("stochastic_oscillator")
    )
    .collect()
)

All surfaces are bit-identical via the single Next<T> implementation and proptests.

Edge Cases & Limitations

  • Warm-up: first 5 bars may return NaN or partial state per implementation.
  • Parameter sensitivity: smaller periods increase noise; larger periods increase lag.
  • Sudden gaps or bad ticks can distort rolling windows — consider pre-filtering.
  • Single-series indicators ignore volume unless otherwise documented.
  • Validated via proptests against gold-standard vectors where available.
  • No look-ahead bias; streaming and Polars batch paths are bit-identical.

Boundary Behavior

Condition Behavior
Warm-up Leading bars return NaN until warmup_bars is satisfied.
period > len When period exceeds series length, output is all NaN.
NaN inputs NaN in input propagates to output (NaN out).
Invalid params Non-positive period or missing required params raise ValueError.
Empty data Empty input returns an empty result series.

Sources & References

Primary Source: https://www.investopedia.com/terms/s/stochasticoscillator.asp

Implementation: quantwave-core/src/indicators/momentum.rs (STOCH / STOCH_METADATA). Parity: quantwave-core/tests/gold_standard/stoch.json

Provenance: Standards bulk upgrade 2026-06-25 IST — see docs/DOCUMENTATION_STANDARDS.md.