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Relative Strength Index (RSI)

Classic momentum oscillator overbought oversold classic

A momentum oscillator that measures the speed and change of price movements.

Visual Example

Relative Strength Index (RSI) — 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 Relative Strength Index (RSI) indicator is a technical analysis tool that a momentum oscillator that measures the speed and change of price movements.

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 overbought (>70) and oversold (<30) conditions. RSI divergences against price often signal impending trend reversals.

Developed by J. Welles Wilder in New Concepts in Technical Trading Systems (1978), the RSI compares the magnitude of recent gains to recent losses to determine overbought and oversold conditions of an asset. It remains the most widely used momentum oscillator in modern technical analysis.

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):

\[ RS = \frac{Average Gain}{Average Loss} \\ RSI = 100 - \frac{100}{1 + RS} \]

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

Parameters

Parameter Default Description
timeperiod 14 Lookback period

Usage Examples

Streaming (Rust)

use quantwave_core::indicators::RSI;
use quantwave_core::traits::Next;

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

Streaming (Python)

from quantwave import RSI

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

Polars Batch (Python)

import polars as pl

df = (
    pl.read_csv('ohlcv.csv')
    .lazy()
    .with_columns(
        pl.col("close").ta.rsi(14).alias("relative_strength_index_rsi")
    )
    .collect()
)

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

Edge Cases & Limitations

  • Warm-up: first 14 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/r/rsi.asp

Implementation: quantwave-core/src/indicators/momentum.rs (RSI / RSI_METADATA). Parity: quantwave-core/tests/gold_standard/rsi.json

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