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
freqtrade/freqtrade-strategies
this is an example class, implementing a PSAR based trailing stop loss you are supposed to take the `custom_stoploss()` and `populate_indicators()` parts and adapt it to your own strategy
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
# ══════════════════════════════════════════════════════════════
# anis solidscale - Elite Spot Trading Suite
# STRATEGIE : RSIDivergence
# CATEGORIE : Mean Reversion — RSI Bullish Divergence
# ══════════════════════════════════════════════════════════════
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 RSIDivergence(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 ──
rsi_period = IntParameter(10, 20, default=14, space="buy")
swing_lookback = IntParameter(5, 15, default=10, space="buy")
ema_filter = IntParameter(30, 60, default=50, space="buy")
# ── Sell params ──
rsi_exit = IntParameter(65, 80, default=75, 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="RSIDivergence")
self._notifier = TelegramNotifier()
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
self._init_utils()
for rsi_p in range(self.rsi_period.low, self.rsi_period.high + 1):
dataframe = CommonIndicators.add_rsi(dataframe, period=rsi_p)
for ema_p in range(self.ema_filter.low, self.ema_filter.high + 1):
dataframe = CommonIndicators.add_ema(dataframe, period=ema_p)
dataframe = CommonIndicators.add_volume_sma(dataframe, period=20)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
rsi_col = f"rsi_{self.rsi_period.value}"
ema_col = f"ema_{self.ema_filter.value}"
lb = self.swing_lookback.value
conditions = (
(dataframe["low"] < dataframe["low"].shift(lb))
& (dataframe[rsi_col] > dataframe[rsi_col].shift(lb))
& (dataframe["close"] > dataframe[ema_col])
& (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:
rsi_col = f"rsi_{self.rsi_period.value}"
conditions = (
dataframe[rsi_col] > self.rsi_exit.value
)
dataframe.loc[conditions, "exit_long"] = 1
return dataframe