Timeframe
4h
Direction
Long Only
Stoploss
-6.0%
Trailing Stop
Yes
ROI
0m: 12.0%, 480m: 6.0%, 1440m: 3.0%
Interface Version
3
Startup Candles
100
Indicators
1
freqtrade/freqtrade-strategies
# ══════════════════════════════════════════════════════════════
# anis solidscale - Elite Spot Trading Suite
# STRATEGIE : MACDDivergenceLite
# CATEGORIE : Divergence — MACD (Simplifie)
# ══════════════════════════════════════════════════════════════
# Version simplifiee de MACDDivergence :
# - 2 params : rsi_entry (buy) + rsi_exit (sell)
# - lookback=5, rsi_period=14, volume_period=20, volume_mult=0.8 fixes
# ══════════════════════════════════════════════════════════════
import sys
from pathlib import Path
from pandas import DataFrame
from freqtrade.strategy import IStrategy, IntParameter
sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent))
from utils.indicators import CommonIndicators
from utils.logging_utils import TradeLogger
from utils.telegram_notifier import TelegramNotifier
class MACDDivergenceLite(IStrategy):
INTERFACE_VERSION = 3
can_short = False
timeframe = "4h"
startup_candle_count = 100
minimal_roi = {"0": 0.12, "480": 0.06, "1440": 0.03}
stoploss = -0.06
trailing_stop = True
trailing_stop_positive = 0.02
trailing_stop_positive_offset = 0.03
trailing_only_offset_is_reached = True
# ── Hyperopt params (1 buy + 1 sell) ──
rsi_entry = IntParameter(30, 55, default=45, space="buy")
rsi_exit = IntParameter(60, 80, default=70, space="sell")
# ── Params fixes ──
LOOKBACK = 5
RSI_PERIOD = 14
VOLUME_PERIOD = 20
VOLUME_MULT = 0.8
_logger = None
_notifier = None
def __getstate__(self):
state = self.__dict__.copy()
state["_logger"] = None
state["_notifier"] = None
return state
def __setstate__(self, state):
self.__dict__.update(state)
def _init_utils(self) -> None:
if self._logger is None:
self._logger = TradeLogger(strategy_name="MACDDivergenceLite")
self._notifier = TelegramNotifier()
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
self._init_utils()
dataframe = CommonIndicators.add_rsi(dataframe, period=self.RSI_PERIOD)
dataframe = CommonIndicators.add_volume_sma(dataframe, period=self.VOLUME_PERIOD)
dataframe = CommonIndicators.add_macd(dataframe)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
rsi_col = f"rsi_{self.RSI_PERIOD}"
vol_sma_col = f"volume_sma_{self.VOLUME_PERIOD}"
lb = self.LOOKBACK
price_lower_low = dataframe["close"] < dataframe["close"].shift(lb)
macd_higher_low = dataframe["macd_histogram"] > dataframe["macd_histogram"].shift(lb)
conditions = (
price_lower_low
& macd_higher_low
& (dataframe[rsi_col] < self.rsi_entry.value)
& (dataframe["volume"] > dataframe[vol_sma_col] * self.VOLUME_MULT)
)
dataframe.loc[conditions, "enter_long"] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
rsi_col = f"rsi_{self.RSI_PERIOD}"
macd_declining_3 = (
(dataframe["macd_histogram"] < 0)
& (dataframe["macd_histogram"] < dataframe["macd_histogram"].shift(1))
& (dataframe["macd_histogram"].shift(1) < dataframe["macd_histogram"].shift(2))
)
conditions = macd_declining_3 | (dataframe[rsi_col] > self.rsi_exit.value)
dataframe.loc[conditions, "exit_long"] = 1
return dataframe