Timeframe
4h
Direction
Long Only
Stoploss
-6.0%
Trailing Stop
Yes
ROI
0m: 10.0%, 240m: 5.0%, 720m: 3.0%, 1440m: 1.0%
Interface Version
3
Startup Candles
80
Indicators
0
freqtrade/freqtrade-strategies
# ══════════════════════════════════════════════════════════════
# anis solidscale - Elite Spot Trading Suite
# STRATEGIE : DMICrossoverLite
# CATEGORIE : Trend — +DI/-DI Crossover (Simplifie)
# ══════════════════════════════════════════════════════════════
# Version simplifiee de DMICrossover :
# - 2 params : dmi_period (buy) + adx_exit (sell)
# - adx_threshold=25 fixe
# ══════════════════════════════════════════════════════════════
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 DMICrossoverLite(IStrategy):
INTERFACE_VERSION = 3
can_short = False
timeframe = "4h"
startup_candle_count = 80
minimal_roi = {"0": 0.10, "240": 0.05, "720": 0.03, "1440": 0.01}
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) ──
dmi_period = IntParameter(10, 20, default=14, space="buy")
adx_exit = IntParameter(15, 30, default=20, space="sell")
# ── Params fixes ──
ADX_THRESHOLD = 25
_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="DMICrossoverLite")
self._notifier = TelegramNotifier()
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
self._init_utils()
for p in range(self.dmi_period.low, self.dmi_period.high + 1):
dataframe = CommonIndicators.add_dmi(dataframe, period=p)
dataframe = CommonIndicators.add_adx(dataframe, period=p)
dataframe = CommonIndicators.add_volume_sma(dataframe, period=20)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
plus_di = f"plus_di_{self.dmi_period.value}"
minus_di = f"minus_di_{self.dmi_period.value}"
adx_col = f"adx_{self.dmi_period.value}"
conditions = (
(dataframe[plus_di] > dataframe[minus_di])
& (dataframe[plus_di].shift(1) <= dataframe[minus_di].shift(1))
& (dataframe[adx_col] > self.ADX_THRESHOLD)
& (dataframe["close"] > dataframe["open"])
& (dataframe["volume"] > 0)
)
dataframe.loc[conditions, "enter_long"] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
plus_di = f"plus_di_{self.dmi_period.value}"
minus_di = f"minus_di_{self.dmi_period.value}"
adx_col = f"adx_{self.dmi_period.value}"
conditions = (
(
(dataframe[plus_di] < dataframe[minus_di])
& (dataframe[plus_di].shift(1) >= dataframe[minus_di].shift(1))
)
| (dataframe[adx_col] < self.adx_exit.value)
)
dataframe.loc[conditions, "exit_long"] = 1
return dataframe