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On-Balance Volume (OBV)

Classic volume momentum classic accumulation distribution

A momentum indicator that uses volume flow to predict changes in stock price.

Visual Example

On-Balance Volume (OBV) — 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 On-Balance Volume (OBV) indicator is a technical analysis tool that a momentum indicator that uses volume flow to predict changes in stock price.

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 accumulation by institutions. When price is flat but OBV is rising, a breakout to the upside is likely. Conversely, when price is flat but OBV is falling, a breakdown is likely.

Introduced by Joe Granville in his 1963 book 'Granville's New Key to Stock Market Profits', OBV is one of the oldest and most respected volume indicators. It operates on the principle that volume precedes price, and that institutional money flow leaves a detectable trail in the volume data before the price move occurs. — 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/volume.rs):

\[ OBV_t = OBV_{t-1} + \begin{cases} Volume & \text{if } Close_t > Close_{t-1} \\ 0 & \text{if } Close_t = Close_{t-1} \\ -Volume & \text{if } Close_t < Close_{t-1} \end{cases} \]

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

Parameters

Parameter Default Description
(none) — No tunable parameters for this detector.

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::OBV;
use quantwave_core::traits::Next;

let mut ind = OBV::new(14);
for price in &prices {
    let value = ind.next(price);
}

Streaming (Python)

from quantwave import OBV

ind = OBV(14)
for price in prices:
    value = ind.next(price)

Polars Batch (Python)

import polars as pl
import quantwave as qw

def apply_on_balance_volume_obv(series: pl.Series) -> pl.Series:
    ind = qw.OBV(14)
    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_on_balance_volume_obv, return_dtype=pl.Float64).alias("on_balance_volume_obv")
    )
    .collect()
)

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

Edge Cases & Limitations

  • Warm-up: first N 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 Output starts from bar 1; warmup_bars marks period-stability, not NaN.
period > len Cumulative sum continues; period only affects smoothed variants.
NaN inputs NaN inputs may produce NaN or skip depending on indicator.
Invalid params Invalid params raise ValueError.
Empty data Empty input returns an empty result series.

Sources & References

Primary Source: https://www.investopedia.com/terms/o/onbalancevolume.asp

Implementation: quantwave-core/src/indicators/volume.rs (OBV / OBV_METADATA). Parity: quantwave-core/tests/gold_standard/obv.json

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