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Three White Soldiers

Patterns candlestick reversal bullish

A three-candle bullish reversal pattern consisting of three consecutive long green (bullish) bodies. Each candle opens inside the prior body and closes near its own high, forming a steady upward staircase that frequently terminates a downtrend.

Visual Example

Three White Soldiers: three successive long green candles, each opening inside the previous body and closing near its high. Annotations mark the progressive higher closes.

Synthetic ideal satisfying TA-Lib CDL3WHITESOLDIERS stepping logic. Generated 2026-05-31 IST via docs/gen_candle_previews.py.

Description

The mirror image of Three Black Crows. Sustained buying over three periods with no meaningful pullback produces a high-conviction bullish reversal signal when it appears after a decline and at support or a Market Structure level.

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.

Used in quant workflows as a strong long-event feature or regime label.

Formula / Specification

Recognition Rules (exact implementation in QuantWave / TA-Lib CDL3WHITESOLDIERS):

  1. Three consecutive green bodies (close > open).
  2. Each opens inside the body of the prior bar.
  3. Each closes near its own high.
  4. Completes on bar 3.
  5. Three-bar state in streaming wrapper.

Parameters

Parameter Default Description
(none) — Pattern recognition only; no tunable parameters.

Usage Examples

Streaming / Polars identical in form to Three Black Crows (substitute the CDL3WHITESOLDIERS type / .ta.cdl_3whitesoldiers(...) method). Guaranteed parity.

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 Pattern functions emit 0 (no pattern) until enough bars exist.
period > len Short series returns all zeros (no pattern detected).
NaN inputs Bars with NaN OHLC are treated as no pattern (0).
Invalid params N/A for most candlestick patterns.
Empty data Empty input returns an empty integer series.

Sources & References

Primary Source: TA-Lib CDL3WHITESOLDIERS via core pattern.rs.

Visual: gen script 2026-05-31 IST.

Context: Nison (1991) staircase buying psychology only; MQL5 PA.

Provenance: Next + Polars fidelity.