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
2
# ══════════════════════════════════════════════════════════════
# anis solidscale - Elite Spot Trading Suite
# STRATEGIE : CCIMomentumTrend
# CATEGORIE : Momentum — CCI Deviation Statistique
# ══════════════════════════════════════════════════════════════
#
# LOGIQUE :
# CCI mesure la deviation du prix par rapport a sa moyenne.
# 1. CCI crossover +100 (momentum fort)
# 2. CCI > +100 pendant 2 bougies (filtre persistence)
# 3. EMA trend filter + volume
# 4. Sortie : CCI < 0 (zero-crossing)
# ══════════════════════════════════════════════════════════════
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 CCIMomentumTrend(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
# ── Buy params ──
cci_period = IntParameter(10, 30, default=20, space="buy")
cci_entry = IntParameter(80, 150, default=100, space="buy")
ema_period = IntParameter(30, 70, default=50, space="buy")
persistence = IntParameter(1, 4, default=2, space="buy")
# ── Sell params ──
cci_exit = IntParameter(-20, 20, default=0, space="sell")
_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="CCIMomentumTrend")
self._notifier = TelegramNotifier()
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
self._init_utils()
for p in range(self.cci_period.low, self.cci_period.high + 1):
dataframe = CommonIndicators.add_cci(dataframe, period=p)
for p in range(self.ema_period.low, self.ema_period.high + 1):
dataframe = CommonIndicators.add_ema(dataframe, period=p)
dataframe = CommonIndicators.add_volume_sma(dataframe, period=20)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
cci_col = f"cci_{self.cci_period.value}"
ema_col = f"ema_{self.ema_period.value}"
persist = self.persistence.value
threshold = self.cci_entry.value
# CCI > threshold pendant 'persist' bougies consecutives
cci_above = dataframe[cci_col] > threshold
for i in range(1, persist):
cci_above = cci_above & (dataframe[cci_col].shift(i) > threshold)
conditions = (
cci_above
& (dataframe["close"] > dataframe[ema_col])
& (dataframe["volume"] > dataframe["volume_sma_20"])
& (dataframe["volume"] > 0)
)
dataframe.loc[conditions, "enter_long"] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
cci_col = f"cci_{self.cci_period.value}"
conditions = (
dataframe[cci_col] < self.cci_exit.value
)
dataframe.loc[conditions, "exit_long"] = 1
return dataframe