Timeframe
1h
Direction
Long Only
Stoploss
-5.0%
Trailing Stop
Yes
ROI
0m: 8.0%, 240m: 4.0%, 720m: 2.0%
Interface Version
3
Startup Candles
50
Indicators
2
# ══════════════════════════════════════════════════════════════
# anis solidscale - Elite Spot Trading Suite
# STRATÉGIE : WilliamsRBounce
# CATÉGORIE : Nouvelle — Mean Reversion Oscillateur
# ══════════════════════════════════════════════════════════════
#
# LOGIQUE :
# Williams %R mesure la position du close par rapport au range.
# 1. Williams %R < -80 → zone de survente
# 2. Close > EMA rapide → confirmation du rebond
# 3. Sortie : Williams %R > -20 (suracheté) OU close < EMA mid
# ══════════════════════════════════════════════════════════════
import sys
from pathlib import Path
from pandas import DataFrame
from freqtrade.strategy import IStrategy, IntParameter, DecimalParameter
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 WilliamsRBounce(IStrategy):
INTERFACE_VERSION = 3
can_short = False
timeframe = "1h"
startup_candle_count = 50
minimal_roi = {"0": 0.08, "240": 0.04, "720": 0.02}
stoploss = -0.05
trailing_stop = True
trailing_stop_positive = 0.015
trailing_stop_positive_offset = 0.025
trailing_only_offset_is_reached = True
# ── Buy params ──
wr_period = IntParameter(7, 21, default=14, space="buy")
ema_fast = IntParameter(5, 15, default=9, space="buy")
ema_mid = IntParameter(15, 30, default=20, space="buy")
wr_entry = IntParameter(-90, -70, default=-80, space="buy")
volume_period = IntParameter(10, 50, default=20, space="buy")
volume_mult = DecimalParameter(0.5, 2.0, default=1.0, decimals=1, space="buy")
# ── Sell params ──
wr_exit = IntParameter(-30, -10, default=-20, space="sell")
_logger = None
_notifier = None
def _init_utils(self) -> None:
if self._logger is None:
self._logger = TradeLogger(strategy_name="WilliamsRBounce")
self._notifier = TelegramNotifier()
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
self._init_utils()
dataframe = CommonIndicators.add_ema(dataframe, period=self.ema_fast.value)
dataframe = CommonIndicators.add_ema(dataframe, period=self.ema_mid.value)
dataframe = CommonIndicators.add_volume_sma(dataframe, period=self.volume_period.value)
# Williams %R calc manuelle
wr_p = self.wr_period.value
highest_high = dataframe["high"].rolling(window=wr_p).max()
lowest_low = dataframe["low"].rolling(window=wr_p).min()
dataframe["williams_r"] = ((highest_high - dataframe["close"]) / (highest_high - lowest_low)) * -100
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
ema_f = f"ema_{self.ema_fast.value}"
vol_col = f"volume_ratio_{self.volume_period.value}"
conditions = (
(dataframe["williams_r"] < self.wr_entry.value)
& (dataframe["close"] > dataframe[ema_f])
& (dataframe[vol_col] > self.volume_mult.value)
& (dataframe["volume"] > 0)
)
dataframe.loc[conditions, "enter_long"] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
ema_m = f"ema_{self.ema_mid.value}"
conditions = (
(dataframe["williams_r"] > self.wr_exit.value)
| (dataframe["close"] < dataframe[ema_m])
)
dataframe.loc[conditions, "exit_long"] = 1
return dataframe