HLHB Forex Trend Strategy

Article Strategy library · Author: freqtrade

Summary

The HLHB system is presented as a short-term forex trend strategy. It calculates RSI from the average of each bar's open and close, alongside 5-period and 10-period EMAs and ADX. A long entry is signaled when RSI crosses above 50 and the faster EMA crosses above the slower EMA, with ADX above 25 and nonzero volume. The exit signal requires RSI and the EMA relationship to cross downward under the same ADX and volume conditions.

The implementation also specifies a four-hour timeframe, return-on-investment targets, a broad stop loss, and a trailing stop. These are configuration details rather than evidence that the system is profitable. The document offers no backtest results or discussion of market conditions, transaction costs, or short-side entries. It is therefore best read as a rule set for trend participation whose signals and risk settings need independent evaluation.

Key ideas

The system combines RSI threshold crossings with fast and slow EMA crossovers to signal long entries and exits.
ADX above 25 is required for both entry and exit signals.
RSI is calculated using the midpoint of each bar's open and close.
The strategy configuration uses a four-hour timeframe and includes ROI targets and a trailing stop.
No performance evidence is provided, and the described signals do not specify short entries.

Tags

Forex Trend following Momentum Technical indicators

Full text

# hlhb


# hlhb









The HLHB ("Huck loves her bucks!") System simply aims to catch short-term forex trends.
    More information in https://www.babypips.com/trading/forex-hlhb-system-explained

## Source (GPL-3.0)

```python
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement

import numpy as np  # noqa
import pandas as pd  # noqa
from pandas import DataFrame
from freqtrade.strategy import IStrategy
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib


class hlhb(IStrategy):
    """
    The HLHB ("Huck loves her bucks!") System simply aims to catch short-term forex trends.
    More information in https://www.babypips.com/trading/forex-hlhb-system-explained
    """

    INTERFACE_VERSION: int = 3

    position_stacking = "True"

    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi".
    minimal_roi = {
        "0": 0.6225,
        "703": 0.2187,
        "2849": 0.0363,
        "5520": 0
    }

    # Optimal stoploss designed for the strategy.
    # This attribute will be overridden if the config file contains "stoploss".
    stoploss = -0.3211

    # Trailing stoploss
    trailing_stop = True
    trailing_stop_positive = 0.0117
    trailing_stop_positive_offset = 0.0186
    trailing_only_offset_is_reached = True

    # Optimal timeframe for the strategy.
    timeframe = '4h'

    # Run "populate_indicators()" only for new candle.
    process_only_new_candles = True

    # These values can be overridden in the "ask_strategy" section in the config.
    use_exit_signal = True
    exit_profit_only = False
    ignore_roi_if_entry_signal = True

    # Number of candles the strategy requires before producing valid signals
    startup_candle_count: int = 30

    # Optional order type mapping.
    order_types = {
        'entry': 'limit',
        'exit': 'limit',
        'stoploss': 'market',
        'stoploss_on_exchange': False
    }

    # Optional order time in force.
    order_time_in_force = {
        'entry': 'gtc',
        'exit': 'gtc'
    }

    plot_config = {
        # Main plot indicators (Moving averages, ...)
        'main_plot': {
            'ema5': {},
            'ema10': {},
        },
        'subplots': {
            # Subplots - each dict defines one additional plot
            "RSI": {
                'rsi': {'color': 'red'},
            },
            "ADX": {
                'adx': {},
            }
        }
    }

    def informative_pairs(self):
        return []

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['hl2'] = (dataframe["close"] + dataframe["open"]) / 2

        # Momentum Indicators
        # ------------------------------------

        # RSI
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=10, price='hl2')

        # # EMA - Exponential Moving Average
        dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)

        # ADX
        dataframe['adx'] = ta.ADX(dataframe)

        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (qtpylib.crossed_above(dataframe['rsi'], 50)) &
                (qtpylib.crossed_above(dataframe['ema5'], dataframe['ema10'])) &
                (dataframe['adx'] > 25) &
                (dataframe['volume'] > 0)  # Make sure Volume is not 0
            ),
            'enter_long'] = 1

        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (qtpylib.crossed_below(dataframe['rsi'], 50)) &
                (qtpylib.crossed_below(dataframe['ema5'], dataframe['ema10'])) &
                (dataframe['adx'] > 25) &
                (dataframe['volume'] > 0)  # Make sure Volume is not 0
            ),
            'exit_long'] = 1
        return dataframe


```

Shown in full with attribution under the source's licence. Licence: GPL-3.0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.

HLHB Forex Trend Strategy with RSI, EMA Crossovers, and ADX

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