# source: https://raw.githubusercontent.com/teguh11/botbot2/b6a117c10497dc2f567d40f8f5054691a76b4665/user_data/strategies/SupertrendSD.py # pragma pylint: disable=missing-docstring, invalid-name, too-many-instance-attributes """ Github_teguh11_botbot2__SupertrendSD__20260713_092552 — SuperTrend + Supply/Demand multi-timeframe strategy. Konsep (dari analisa chart TradingView): • SuperTrend 4H → filter arah (bull → hanya LONG, bear → hanya SHORT) • SuperTrend 15m → trigger entry saat flip searah dengan 4H • Volume spike → konfirmasi reversal (replika marker "R" volume-tinggi) • Supply/Demand → swing high/low terdekat sebagai konteks S/R """ from datetime import datetime from typing import Optional import numpy as np import pandas as pd from pandas import DataFrame import talib.abstract as ta from freqtrade.strategy import ( IStrategy, informative, DecimalParameter, IntParameter, ) from freqtrade.persistence import Trade def supertrend(dataframe: DataFrame, period: int = 10, multiplier: float = 3.0): """ Return (st_line, direction). direction: +1 = bullish (garis hijau di bawah harga), -1 = bearish (garis merah di atas harga). """ df = dataframe atr = ta.ATR(df, timeperiod=period) hl2 = (df["high"] + df["low"]) / 2 upper = np.asarray(hl2 + multiplier * atr, dtype="float64").copy() lower = np.asarray(hl2 - multiplier * atr, dtype="float64").copy() close = np.asarray(df["close"], dtype="float64") n = len(df) in_up = np.ones(n, dtype=bool) for i in range(1, n): if close[i] > upper[i - 1]: in_up[i] = True elif close[i] < lower[i - 1]: in_up[i] = False else: in_up[i] = in_up[i - 1] # Band hanya boleh mengetat searah tren (trailing) if in_up[i] and lower[i] < lower[i - 1]: lower[i] = lower[i - 1] if (not in_up[i]) and upper[i] > upper[i - 1]: upper[i] = upper[i - 1] st_line = np.where(in_up, lower, upper) direction = np.where(in_up, 1, -1) return ( pd.Series(st_line, index=df.index), pd.Series(direction, index=df.index), ) class Github_teguh11_botbot2__SupertrendSD__20260713_092552(IStrategy): INTERFACE_VERSION = 3 timeframe = "15m" can_short = True # ROI & stoploss (dasar — bisa di-hyperopt nanti) minimal_roi = { "0": 0.05, "30": 0.03, "60": 0.02, "120": 0.0, } stoploss = -0.08 trailing_stop = True trailing_stop_positive = 0.02 trailing_stop_positive_offset = 0.03 trailing_only_offset_is_reached = True process_only_new_candles = True use_exit_signal = True exit_profit_only = False ignore_roi_if_entry_signal = False startup_candle_count = 200 # ── Hyperparameters ─────────────────────────────────────── st_period = IntParameter(7, 20, default=10, space="buy") st_mult = DecimalParameter(1.5, 4.0, default=3.0, decimals=1, space="buy") vol_factor = DecimalParameter(1.0, 2.5, default=1.3, decimals=1, space="buy") adx_min = IntParameter(15, 40, default=25, space="buy") leverage_num = IntParameter(1, 10, default=5, space="buy") # ── Higher timeframe: SuperTrend 4H (filter arah) ───────── @informative("4h") def populate_indicators_4h(self, dataframe: DataFrame, metadata: dict) -> DataFrame: _, st_dir = supertrend(dataframe, self.st_period.value, self.st_mult.value) dataframe["st_dir"] = st_dir return dataframe # ── Base timeframe: 15m ─────────────────────────────────── def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: st_line, st_dir = supertrend(dataframe, self.st_period.value, self.st_mult.value) dataframe["st_line"] = st_line dataframe["st_dir"] = st_dir # Flip = titik reversal dataframe["st_flip_up"] = (st_dir == 1) & (st_dir.shift(1) == -1) dataframe["st_flip_down"] = (st_dir == -1) & (st_dir.shift(1) == 1) # Volume spike (konfirmasi "R") dataframe["vol_ma"] = dataframe["volume"].rolling(20).mean() dataframe["vol_spike"] = dataframe["volume"] > (self.vol_factor.value * dataframe["vol_ma"]) # Supply/Demand konteks — swing high/low 20 candle dataframe["demand"] = dataframe["low"].rolling(20).min() dataframe["supply"] = dataframe["high"].rolling(20).max() # Filter tren dasar dataframe["ema200"] = ta.EMA(dataframe, timeperiod=200) dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14) dataframe["adx"] = ta.ADX(dataframe, timeperiod=14) # kekuatan tren return dataframe # ── Entry ───────────────────────────────────────────────── def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: long_cond = ( dataframe["st_flip_up"] # 15m flip bullish & (dataframe["st_dir_4h"] == 1) # 4H tren bullish & dataframe["vol_spike"] # volume konfirmasi & (dataframe["adx"] > self.adx_min.value) # tren cukup kuat (anti-chop) & (dataframe["rsi"] < 70) & (dataframe["volume"] > 0) ) dataframe.loc[long_cond, ["enter_long", "enter_tag"]] = (1, "st_flip_long") short_cond = ( dataframe["st_flip_down"] # 15m flip bearish & (dataframe["st_dir_4h"] == -1) # 4H tren bearish & dataframe["vol_spike"] # volume konfirmasi & (dataframe["adx"] > self.adx_min.value) # tren cukup kuat (anti-chop) & (dataframe["rsi"] > 30) & (dataframe["volume"] > 0) ) dataframe.loc[short_cond, ["enter_short", "enter_tag"]] = (1, "st_flip_short") return dataframe # ── Exit ────────────────────────────────────────────────── def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Keluar saat SuperTrend 15m flip berlawanan dataframe.loc[dataframe["st_flip_down"], "exit_long"] = 1 dataframe.loc[dataframe["st_flip_up"], "exit_short"] = 1 return dataframe # ── Leverage ────────────────────────────────────────────── def leverage(self, pair: str, current_time: datetime, current_rate: float, proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str, **kwargs) -> float: return float(min(self.leverage_num.value, max_leverage))