Market Structure Break

Warmup Window

Minimum bars needed: 2 × pivot_length + 1 bars (default params: 15 bars (pivot_length=7))

Pivot points need pivot_length bars on each side. Once the first pivots are confirmed, break signals fire in real-time.

✅ After the warmup window is filled, this indicator produces a new value on every incoming bar in real-time.

Real-time Indicator

Structure breaks fire after pivot confirmation, not after smoothing delay.

Event	Lag	Detail
Break signal fires	≈ `pivot_length` bars after the pivot	Pivot needs pivot_length bars on each side; signal fires when close breaks past the pivot

Market Structure Break (MSB) is a Smart Money Concept (SMC) indicator that detects when price breaks through significant pivot points, signaling potential trend changes. Combined with Order Block detection and quality scoring, this tool helps identify high-probability trading zones.

Market Structure Break (MSB):

Bullish MSB: Price closes above the last pivot high, indicating potential bullish momentum
Bearish MSB: Price closes below the last pivot low, indicating potential bearish momentum

Order Block Quality Score (0-100):

Based on momentum z-score and volume percentile
Score > 80 indicates a High Probability Zone (HPZ)

Best Use Cases:

Pullback/retracement trading (enter at OB zones after MSB)
Multi-timeframe analysis (use higher TF for bias, lower TF for entries)
Supply & demand zone trading

def market_structure_break(
    data: Union[PdDataFrame, PlDataFrame],
    pivot_length: int = 7,
    momentum_zscore_threshold: float = 0.5,
    high_column: str = 'High',
    low_column: str = 'Low',
    close_column: str = 'Close',
    volume_column: str = 'Volume',
    msb_bullish_column: str = 'msb_bullish',
    msb_bearish_column: str = 'msb_bearish',
    last_pivot_high_column: str = 'last_pivot_high',
    last_pivot_low_column: str = 'last_pivot_low',
    momentum_z_column: str = 'momentum_z'
) -> Union[PdDataFrame, PlDataFrame]:

def market_structure_ob(
    data: Union[PdDataFrame, PlDataFrame],
    pivot_length: int = 7,
    momentum_zscore_threshold: float = 0.5,
    max_active_obs: int = 10,
    ...
) -> Union[PdDataFrame, PlDataFrame]:

Example

import pandas as pd
from pyindicators import (
    market_structure_break,
    market_structure_ob,
    get_market_structure_stats
)

# Create sample OHLC data
df = pd.DataFrame({
    'Open': [...],
    'High': [...],
    'Low': [...],
    'Close': [...],
    'Volume': [...]
})

# Basic MSB detection
df = market_structure_break(df, pivot_length=5)
print(df[['msb_bullish', 'msb_bearish', 'last_pivot_high', 'last_pivot_low']])

# MSB with Order Block detection and quality scoring
df = market_structure_ob(df, pivot_length=5)
print(df[['msb_bullish', 'msb_bearish', 'ob_bullish', 'ob_bearish', 'ob_quality', 'ob_is_hpz']])

# Get statistics
stats = get_market_structure_stats(df)
print(f"Reliability: {stats['reliability']:.1f}%")
print(f"HPZ Count: {stats['hpz_count']}")
print(f"Bullish MSBs: {stats['bullish_msb_count']}")
print(f"Bearish MSBs: {stats['bearish_msb_count']}")

The market_structure_break function returns:

msb_bullish / msb_bearish: 1 when MSB detected, 0 otherwise
last_pivot_high / last_pivot_low: Most recent pivot levels
momentum_z: Momentum z-score value

The market_structure_ob function additionally returns:

ob_bullish / ob_bearish: 1 when Order Block detected at MSB
ob_top / ob_bottom: Order Block zone boundaries
ob_quality: Quality score (0-100)
ob_is_hpz: True if quality > 80 (High Probability Zone)
ob_mitigated: 1 when Order Block has been mitigated

Recommended Parameters by Timeframe:

Timeframe	pivot_length	Use Case
1m-5m	2-3	Scalping entries
15m	3-5	Day trading
1H	5-7	Swing confirmation
4H-Daily	7-10	Trend direction

MARKET_STRUCTURE

Chart Parameters

The image above uses the following parameters:

Parameter	Value
`pivot_length`	`7`