Trendline Breakout Navigator

The Trendline Breakout Navigator is a multi-timeframe trendline detection indicator. It detects pivot highs and lows at three swing lengths (long, medium, short), constructs trendlines on HH/LL trend reversals, and tracks trendline breakouts and wick interactions.

def trendline_breakout_navigator(
    data: Union[PdDataFrame, PlDataFrame],
    swing_long: int = 60,
    swing_medium: int = 30,
    swing_short: int = 10,
    enable_long: bool = True,
    enable_medium: bool = True,
    enable_short: bool = True,
    high_column: str = "High",
    low_column: str = "Low",
    close_column: str = "Close",
) -> Union[PdDataFrame, PlDataFrame]:

Returns the following columns:

tbn_trend_long / tbn_trend_medium / tbn_trend_short: Trend direction per timeframe (1 = bullish, −1 = bearish, 0 = undetermined)
tbn_value_long / tbn_value_medium / tbn_value_short: Projected trendline price per timeframe
tbn_slope_long / tbn_slope_medium / tbn_slope_short: Trendline slope per bar per timeframe
tbn_wick_bull / tbn_wick_bear: Wick break flags (bullish / bearish)
tbn_hh / tbn_ll: Higher High / Lower Low confirmation flags
tbn_composite_trend: Sum of all enabled timeframe trends (−3 to +3)

Signal function:

tbn_signal: 1 = bullish (composite > 0), -1 = bearish (composite < 0), 0 = neutral

from investing_algorithm_framework import download

from pyindicators import (
    trendline_breakout_navigator,
    trendline_breakout_navigator_signal,
    get_trendline_breakout_navigator_stats,
)

pd_df = download(
    symbol="btc/eur",
    market="bitvavo",
    time_frame="4h",
    start_date="2024-01-01",
    end_date="2024-06-01",
    pandas=True,
)

# Detect trendlines and breakouts
pd_df = trendline_breakout_navigator(pd_df, swing_long=60, swing_medium=30, swing_short=10)
pd_df = trendline_breakout_navigator_signal(pd_df)

# Get summary statistics
stats = get_trendline_breakout_navigator_stats(pd_df)
print(stats)

pd_df[["Close", "tbn_trend_long", "tbn_value_long", "tbn_composite_trend",
       "tbn_wick_bull", "tbn_wick_bear", "tbn_hh", "tbn_ll", "tbn_signal"]].tail(10)

Pattern Recognition​

Pattern Recognition