# source: https://raw.githubusercontent.com/nicnl31/pyalgotrader/c22b45dc6744b8dc3ea5c9e73858c81274686684/frameworks/freqtrade/user_data/strategies/BigTrader.py # --- Do not remove these libs --- from freqtrade.strategy.interface import IStrategy from freqtrade.strategy import merge_informative_pair from typing import Dict, List from functools import reduce from pandas import DataFrame # -------------------------------- import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib import datetime from technical.util import resample_to_interval, resampled_merge from datetime import datetime, timedelta from freqtrade.persistence import Trade from freqtrade.strategy import stoploss_from_open # BASED ON SMAOffset by Tirail. # MOD BY Czaruś # Backtested with 1 max open trade on Binance with USDT pairs, 5m timeframe. # This strat trades once a day or once every other day. # # # ======================================================= SELL REASON STATS ======================================================== # | Sell Reason | Sells | Win Draws Loss Win% | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | # |--------------------+---------+--------------------------+----------------+----------------+-------------------+----------------| # | trailing_stop_loss | 39 | 39 0 0 100 | 3.49 | 136.09 | 28862.4 | 136.09 | # | roi | 1 | 1 0 0 100 | 8.99 | 8.99 | 1977.06 | 8.99 | # ====================================================== LEFT OPEN TRADES REPORT ====================================================== # | Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | # |--------+--------+----------------+----------------+-------------------+----------------+----------------+-------------------------| # | TOTAL | 0 | 0.00 | 0.00 | 0.000 | 0.00 | 0:00 | 0 0 0 0 | # ================== SUMMARY METRICS =================== # | Metric | Value | # |------------------------+---------------------------| # | Backtesting from | 2021-04-30 00:00:00 | # | Backtesting to | 2021-07-27 08:35:00 | # | Max open trades | 1 | # | | | # | Total/Daily Avg Trades | 40 / 0.45 | # | Starting balance | 10000.000 USDT | # | Final balance | 40839.439 USDT | # | Absolute profit | 30839.439 USDT | # | Total profit % | 308.39% | # | Avg. stake amount | 19858.310 USDT | # | Total trade volume | 794332.392 USDT | # | | | # | Best Pair | DATA/USDT 20.44% | # | Worst Pair | ADA/USDT 0.0% | # | Best trade | ONG/USDT 8.99% | # | Worst trade | ETC/USDT 2.2% | # | Best day | 5198.630 USDT | # | Worst day | 0.000 USDT | # | Days win/draw/lose | 18 / 42 / 0 | # | Avg. Duration Winners | 11:22:00 | # | Avg. Duration Loser | 0:00:00 | # | Rejected Buy signals | 536137 | # | | | # | Min balance | 0.000 USDT | # | Max balance | 0.000 USDT | # | Drawdown | 0.0% | # | Drawdown | 0.000 USDT | # | Drawdown high | 0.000 USDT | # | Drawdown low | 0.000 USDT | # | Drawdown Start | 1970-01-01 00:00:00+00:00 | # | Drawdown End | 1970-01-01 00:00:00+00:00 | # | Market change | -53.09% | # ====================================================== low_offset = 0.958 # something lower than 1 high_offset = 1.012 # something higher than 1 class Github_nicnl31_pyalgotrader__BigTrader__20240902_122600(IStrategy): INTERFACE_VERSION = 2 # ROI table: minimal_roi = { "0": 0.09, } # Stoploss: stoploss = -0.5 # Trailing stop: trailing_stop = True trailing_stop_positive = 0.005 trailing_stop_positive_offset = 0.029 trailing_only_offset_is_reached = True # Sell signal use_sell_signal = True sell_profit_only = True sell_profit_offset = 0.01 ignore_roi_if_buy_signal = True # Optimal timeframe for the strategy timeframe = '5m' # Run "populate_indicators()" only for new candle. process_only_new_candles = True # Number of candles the strategy requires before producing valid signals startup_candle_count: int = 60 # Optional order type mapping. order_types = { 'buy': 'market', 'sell': 'market', 'stoploss': 'market', 'stoploss_on_exchange': True } # Optional order time in force. order_time_in_force = { 'buy': 'gtc', 'sell': 'gtc' } plot_config = { 'main_plot': { 'tema': {}, 'sar': {'color': 'white'}, }, 'subplots': { "MACD": { 'macd': {'color': 'blue'}, 'macdsignal': {'color': 'orange'}, }, "RSI": { 'rsi': {'color': 'red'}, } } } # def informative_pairs(self): # get access to all pairs available in whitelist. # pairs = self.dp.current_whitelist() # Assign tf to each pair so they can be downloaded and cached for strategy. # informative_pairs = [("BTC/USDT", "5m") # ] # return informative_pairs def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # assert self.dp, "DataProvider is required for multiple timeframes." # Get the informative pair # informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=self.timeframe) # SMA # informative['sma_10'] = ta.SMA(informative, timeperiod=10) # informative['sma_4'] = ta.SMA(informative, timeperiod=4) # dataframe = merge_informative_pair(dataframe, informative, self.timeframe, '5m', ffill=True) # dataframe['sma_30'] = ta.SMA(dataframe, timeperiod=30) # dataframe['sma_20'] = ta.SMA(dataframe, timeperiod=20) dataframe['sma_15'] = ta.SMA(dataframe, timeperiod=15) # dataframe['sma_5'] = ta.SMA(dataframe, timeperiod=5) # dataframe['sma_3'] = ta.SMA(dataframe, timeperiod=3) # dataframe['sma_2'] = ta.SMA(dataframe, timeperiod=2) # dataframe['sma_10'] = ta.SMA(dataframe, timeperiod=10) # dataframe['volume_shifted'] = dataframe['volume'].shift(3) # dataframe['volume_shifted_sold'] = dataframe['volume'].shift(4) # dataframe['volume_shifted_buy'] = dataframe['volume'].shift(1) # dataframe['sma_5'] = ta.SMA(dataframe, timeperiod=5) return dataframe def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['close'] < (dataframe['sma_15'] * low_offset)) & (dataframe['close'] > dataframe['close'].shift(4)) & (dataframe['close'].shift(8) > dataframe['close'].shift(4)) & (dataframe['close'].shift(12) > dataframe['close'].shift(8)) & (dataframe['volume'] > 0) ), 'buy'] = 1 return dataframe def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['open'] > (dataframe['sma_15'] * high_offset)) & (dataframe['open'] < dataframe['close'].shift(4)) & (dataframe['close'].shift(8) < dataframe['close'].shift(4)) & (dataframe['close'].shift(12) < dataframe['close'].shift(8)) & (dataframe['volume'] > 0) ), 'sell'] = 1 return dataframe