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
1
freqtrade/freqtrade-strategies
# ══════════════════════════════════════════════════════════════
# anis solidscale - Elite Spot Trading Suite
# STRATEGIE : OBVDivergenceLite
# CATEGORIE : Volume — OBV Divergence (Simplifie)
# ══════════════════════════════════════════════════════════════
# Version simplifiee de OBVDivergence :
# - 2 params : rsi_entry (buy) + rsi_exit (sell)
# - lookback=5, rsi_period=14 fixes
# ══════════════════════════════════════════════════════════════
import sys
from pathlib import Path
import numpy as np
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 OBVDivergenceLite(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) ──
rsi_entry = IntParameter(30, 60, default=50, space="buy")
rsi_exit = IntParameter(60, 85, default=70, space="sell")
# ── Params fixes ──
LOOKBACK = 5
RSI_PERIOD = 14
_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="OBVDivergenceLite")
self._notifier = TelegramNotifier()
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
self._init_utils()
dataframe = CommonIndicators.add_rsi(dataframe, period=self.RSI_PERIOD)
obv_direction = np.where(
dataframe["close"] > dataframe["close"].shift(1), 1,
np.where(dataframe["close"] < dataframe["close"].shift(1), -1, 0)
)
dataframe["obv"] = (dataframe["volume"] * obv_direction).cumsum()
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
rsi_col = f"rsi_{self.RSI_PERIOD}"
lb = self.LOOKBACK
conditions = (
(dataframe["close"] < dataframe["close"].shift(lb))
& (dataframe["obv"] > dataframe["obv"].shift(lb))
& (dataframe[rsi_col] < self.rsi_entry.value)
& (dataframe["volume"] > 0)
)
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}"
lb = self.LOOKBACK
conditions = (
(
(dataframe["close"] > dataframe["close"].shift(lb))
& (dataframe["obv"] < dataframe["obv"].shift(lb))
)
| (dataframe[rsi_col] > self.rsi_exit.value)
)
dataframe.loc[conditions, "exit_long"] = 1
return dataframe