# source: https://raw.githubusercontent.com/Willemstijn/user_data/758a23f80ce7a5dca176e939c4f3f8562d11a304/stratscorer/all_strategies/Stray_kids_strategy_s.py # ============================================================================================== # Stray kids strategy for Spot # # Made by: # ______ _ _ _____ _ ______ _ # | _ \ | | | | / __ \ | | | _ \ | | # | | | | _ _ | |_ ___ | |__ | / \/ _ __ _ _ _ __ | |_ ___ | | | | __ _ __| | # | | | || | | || __|/ __|| '_ \ | | | '__|| | | || '_ \ | __|/ _ \ | | | |/ _` | / _` | # | |/ / | |_| || |_| (__ | | | || \__/\| | | |_| || |_) || |_| (_) || |/ /| (_| || (_| | # |___/ \__,_| \__|\___||_| |_| \____/|_| \__, || .__/ \__|\___/ |___/ \__,_| \__,_| # __/ || | # |___/ |_| # Version : 1.0 # Date : 2023-05 # Remarks : # As published, explained and tested in my Youtube video: # # Visit my site for more information: https://www.dutchalgotrading.com/ # Become my Patron: https://www.patreon.com/dutchalgotrading # - # - # ============================================================================================== # --- Used commands for later reference --- # source .env/bin/activate # freqtrade --version # freqtrade new-config # freqtrade new-strategy --strategy # freqtrade test-pairlist -c user_data/spot_config.json # freqtrade download-data -c user_data/spot_config.json --timerange 20170606- -t 1d 4h 1h 30m 15m 5m 1m # freqtrade backtesting -c user_data/spot_config.json -s github_Willemstijn_user_data__Stray_kids_strategy_s__20230822_152729 --timerange=20190101-20210530 --timeframe=1d # freqtrade backtesting -c user_data/spot_config.json -s github_Willemstijn_user_data__Stray_kids_strategy_s__20230822_152729 --timerange=-20230101 --timeframe=1d # freqtrade backtesting-analysis # freqtrade plot-dataframe -p BTC/USDT:USDT --strategy github_Willemstijn_user_data__Stray_kids_strategy_s__20230822_152729 -c user_data/spot_config.json # freqtrade plot-dataframe -p AXS/USDT:USDT --strategy github_Willemstijn_user_data__Stray_kids_strategy_s__20230822_152729 -c user_data/spot_config.json # freqtrade plot-dataframe -p SOL/USDT:USDT --strategy github_Willemstijn_user_data__Stray_kids_strategy_s__20230822_152729 -c user_data/spot_config.json # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # flake8: noqa: F401 # isort: skip_file # --- Do not remove these libs --- import numpy as np import pandas as pd from pandas import DataFrame from datetime import datetime from typing import Optional, Union from freqtrade.strategy import ( BooleanParameter, CategoricalParameter, DecimalParameter, IntParameter, IStrategy, merge_informative_pair, ) # -------------------------------- # Add your lib to import here import talib.abstract as ta import pandas_ta as pta from technical import qtpylib class github_Willemstijn_user_data__Stray_kids_strategy_s__20230822_152729(IStrategy): # Strategy interface version - allow new iterations of the strategy interface. # Check the documentation or the Sample strategy to get the latest version. INTERFACE_VERSION = 3 # Proposed timeframe for the strategy. Can be altered to your own preferred timeframe. timeframe = "1d" # Can this strategy go short? can_short: bool = False # Minimal ROI designed for the strategy. # Set to 10000% since the exit signal determines the trade exit. # Some crypto even got ROI triggered at 100% so had to set it to this value. minimal_roi = {"0": 100.0} # Optimal stoploss designed for the strategy. # Set to 100% since the exit signal dermines the trade exit. stoploss = -0.25 # Trailing stoploss trailing_stop = False # Run "populate_indicators()" only for new candle. process_only_new_candles = True # These values can be overridden in the config. use_exit_signal = True exit_profit_only = False ignore_roi_if_entry_signal = False # Number of candles the strategy requires before producing valid signals # Set to the default of 30. startup_candle_count: int = 30 # Optional order type mapping. order_types = { "entry": "limit", "exit": "limit", "stoploss": "market", "stoploss_on_exchange": False, } # Optional order time in force. order_time_in_force = {"entry": "GTC", "exit": "GTC"} @property def plot_config(self): return { "main_plot": { 'kijun': {"color": "red"}, # 'st': {"color": "blue"} }, 'subplots': { # Create subplot MACD "zscore": { 'zscore': {'color': 'green', 'type': 'bar', 'plotly': {'opacity': 0.4}} }, }, } def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Z score indicator dataframe['zscore'] = pta.zscore(close = dataframe['close'], length = 14) # Supertrend indicator st_length = 10 st_mult = 5.0 dataframe['st'] = pta.supertrend(high=dataframe['high'], low=dataframe['low'], close=dataframe['close'], length=st_length, multiplier=st_mult)[f'SUPERTd_{st_length}_{st_mult}'] # CREATE ICHIMOKU INDICATOR # Specify the lenghts for each indicator (20, 60, 120, 60 is for crypto trading) TS = 9 KS = 26 SS = 52 CS = 26 OS = 0 # Only create the kijun sen here dataframe["kijun"] = pta.ichimoku( high=dataframe["high"], low=dataframe["low"], close=dataframe["close"], tenkan=TS, kijun=KS, senkou=SS, offset=OS, )[0][f"IKS_{KS}"] # The actual signals are here dataframe['long'] = (dataframe['st'] == 1) & (dataframe['close'] > dataframe['kijun']) & (dataframe['zscore'] > 0) # first check if dataprovider is available if self.dp: if self.dp.runmode.value in ("live", "dry_run"): ob = self.dp.orderbook(metadata["pair"], 1) dataframe["best_bid"] = ob["bids"][0][0] dataframe["best_ask"] = ob["asks"][0][0] # #print(self) #print(metadata) # #print(dataframe[dataframe['long'] == True]) # #print(dataframe[dataframe['short'] == True]) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( # Uncomment this line if you use the dataframe signal column above # (dataframe["long"] == True) & (dataframe["volume"] > 0) # Guard (dataframe['st'] == 1) & (dataframe['zscore'] > 0) & (qtpylib.crossed_above(dataframe['close'], dataframe['kijun'])) # & (dataframe['close'] > dataframe['kijun']) ), ["enter_long", "enter_tag"], ] = (1, "Long _signal") return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( # The exit signal for long trades is pretty straightforward. # Sell when the close price is below the kijun sen # (dataframe["close"] < dataframe["kijun"]) & (dataframe["volume"] > 0) # Guard (qtpylib.crossed_below(dataframe['close'], dataframe['kijun'])) & (dataframe["volume"] > 0) # Guard ), ["exit_long", "exit_tag"], ] = (1, "Long_exit") return dataframe