# source: https://raw.githubusercontent.com/DerSalvador/freqtrade-helm-chart/a669dc11b640b0eb63aa8f8b51e9f181fd7ee43c/chart/deployed_strategies/binance-michael-k8s-namespace/BigZ0407HO.py import freqtrade.vendor.qtpylib.indicators as qtpylib import numpy as np import talib.abstract as ta from freqtrade.persistence import Trade from freqtrade.strategy.interface import IStrategy from pandas import DataFrame, Series from datetime import datetime, timedelta from freqtrade.strategy import merge_informative_pair, CategoricalParameter, DecimalParameter, IntParameter from functools import reduce from technical.indicators import zema ########################################################################################################### ## BigZ04 by ilya ## ## ## ## https://github.com/i1ya/freqtrade-strategies ## ## The stratagy most inspired by iterativ (authors of the CombinedBinHAndClucV6) ## ## ## ## ########################################################################################################### ## The main point of this strat is: ## ## - make drawdown as low as possible ## ## - entry at dip ## ## - exit quick as fast as you can (release money for the next entry) ## ## - soft check if market if rising ## ## - hard check is market if fallen ## ## - 11 entry signals ## ## - stoploss function preventing from big fall ## ## - no exit signal. Whether ROI or stoploss =) ## ## ## ########################################################################################################### ## GENERAL RECOMMENDATIONS ## ## ## ## For optimal performance, suggested to use between 2 and 4 open trades, with unlimited stake. ## ## ## ## As a pairlist you can use VolumePairlist. ## ## ## ## Ensure that you don't override any variables in your config.json. Especially ## ## the timeframe (must be 5m). ## ## ## ## exit_profit_only: ## ## True - risk more (gives you higher profit and higher Drawdown) ## ## False (default) - risk less (gives you less ~10-15% profit and much lower Drawdown) ## ## ## ########################################################################################################### ## DONATIONS 2 @iterativ (author of the original strategy) ## ## ## ## Absolutely not required. However, will be accepted as a token of appreciation. ## ## ## ## BTC: bc1qvflsvddkmxh7eqhc4jyu5z5k6xcw3ay8jl49sk ## ## ETH: 0x83D3cFb8001BDC5d2211cBeBB8cB3461E5f7Ec91 ## ## ## ########################################################################################################### class Github_DerSalvador_freqtrade_helm_chart__BigZ0407HO__20260115_122204(IStrategy): INTERFACE_VERSION = 3 # I feel lucky! # We're going up? minimal_roi = {'0': 0.1, '10': 0.05, '40': 0.02, '180': 0.1} stoploss = -0.99 # effectively disabled. timeframe = '5m' inf_1h = '1h' # Sell signal use_exit_signal = True exit_profit_only = False exit_profit_offset = 0.001 # it doesn't meant anything, just to guarantee there is a minimal profit. ignore_roi_if_entry_signal = False # Trailing stoploss trailing_stop = False trailing_only_offset_is_reached = False trailing_stop_positive = 0.01 trailing_stop_positive_offset = 0.025 # Custom stoploss use_custom_stoploss = True # 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 = 200 # Optional order type mapping. order_types = {'entry': 'market', 'exit': 'market', 'stoploss': 'market', 'stoploss_on_exchange': False} ############# # Enable/Disable conditions entry_params = {'entry_condition_0_enable': True, 'entry_condition_1_enable': True, 'entry_condition_2_enable': True, 'entry_condition_3_enable': True, 'entry_condition_4_enable': True, 'entry_condition_5_enable': True, 'entry_condition_6_enable': True, 'entry_condition_7_enable': True, 'entry_condition_8_enable': True, 'entry_condition_9_enable': True, 'entry_condition_10_enable': True, 'entry_condition_11_enable': True, 'entry_condition_12_enable': True, 'entry_condition_13_enable': True, 'entry_bb20_close_bblowerband_safe_1': 0.931, 'entry_bb20_close_bblowerband_safe_2': 0.978, 'entry_volume_drop_1': 6.0, 'entry_volume_drop_2': 9.5, 'entry_volume_drop_3': 1.0, 'entry_volume_pump_1': 0.4, 'entry_rsi_1h_1': 16.0, 'entry_rsi_1h_2': 15.4, 'entry_rsi_1h_3': 19.1, 'entry_rsi_1h_4': 29.1, 'entry_rsi_1h_5': 59.1, 'entry_rsi_1': 27.5, 'entry_rsi_2': 14.8, 'entry_rsi_3': 13.7, 'entry_macd_1': 0.08, 'entry_macd_2': 0.03, 'entry_condition_12_bblower_close': 0.989, 'entry_condition_12_bblower_low': 0.988, 'entry_condition_12_rsi_1h': 78.4, 'entry_condition_11_close_1': 0.143, 'entry_condition_11_close_2': 0.018, 'entry_condition_11_rsi': 50.27, 'entry_condition_0_close': 1.046, 'entry_condition_0_rsi': 31.7, 'entry_condition_0_rsi_1h': 66.2, 'entry_condition_10_hist_close': 0.0009, 'entry_condition_10_rsi': 40.0, 'entry_condition_1_rsi_1h': 73.1} exit_params = {'custom_stoploss_minutes': 75, 'custom_stoploss_rsi_1h': 36.0, 'custom_stoploss_current_rates_1': 1.032, 'custom_stoploss_current_rates_2': 1.014} ############################################################################ # Buy entry_condition_0_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_1_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_2_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_3_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_4_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_5_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_6_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_7_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_8_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_9_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_10_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_11_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_12_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_condition_13_enable = CategoricalParameter([True, False], default=True, space='entry', optimize=False, load=True) entry_bb20_optimize = False entry_bb20_close_bblowerband_safe_1 = DecimalParameter(0.7, 1.1, default=0.989, space='entry', optimize=entry_bb20_optimize, load=True) entry_bb20_close_bblowerband_safe_2 = DecimalParameter(0.7, 1.1, default=0.982, space='entry', optimize=entry_bb20_optimize, load=True) entry_volume_pump_optimize = False entry_volume_pump_1 = DecimalParameter(0.1, 0.9, default=0.4, space='entry', decimals=1, optimize=entry_volume_pump_optimize, load=True) entry_volume_drop_1 = DecimalParameter(1, 10, default=3.8, space='entry', decimals=1, optimize=entry_volume_pump_optimize, load=True) entry_volume_drop_2 = DecimalParameter(1, 10, default=3, space='entry', decimals=1, optimize=entry_volume_pump_optimize, load=True) entry_volume_drop_3 = DecimalParameter(1, 10, default=2.7, space='entry', decimals=1, optimize=entry_volume_pump_optimize, load=True) entry_rsi_1h_optimize_1 = False entry_rsi_1h_optimize_2 = False entry_rsi_1h_1 = DecimalParameter(10.0, 40.0, default=16.5, space='entry', decimals=1, optimize=entry_rsi_1h_optimize_1, load=True) entry_rsi_1h_2 = DecimalParameter(10.0, 40.0, default=15.0, space='entry', decimals=1, optimize=entry_rsi_1h_optimize_1, load=True) entry_rsi_1h_3 = DecimalParameter(10.0, 40.0, default=20.0, space='entry', decimals=1, optimize=entry_rsi_1h_optimize_1, load=True) entry_rsi_1h_4 = DecimalParameter(10.0, 40.0, default=35.0, space='entry', decimals=1, optimize=entry_rsi_1h_optimize_2, load=True) entry_rsi_1h_5 = DecimalParameter(10.0, 60.0, default=39.0, space='entry', decimals=1, optimize=entry_rsi_1h_optimize_2, load=True) entry_rsi_optimize = False entry_rsi_1 = DecimalParameter(10.0, 40.0, default=28.0, space='entry', decimals=1, optimize=entry_rsi_optimize, load=True) entry_rsi_2 = DecimalParameter(7.0, 40.0, default=10.0, space='entry', decimals=1, optimize=entry_rsi_optimize, load=True) entry_rsi_3 = DecimalParameter(7.0, 40.0, default=14.2, space='entry', decimals=1, optimize=entry_rsi_optimize, load=True) entry_macd_optimize = False entry_macd_1 = DecimalParameter(0.01, 0.09, default=0.02, space='entry', decimals=2, optimize=entry_macd_optimize, load=True) entry_macd_2 = DecimalParameter(0.01, 0.09, default=0.03, space='entry', decimals=2, optimize=entry_macd_optimize, load=True) entry_condition_12_optimize = False entry_condition_12_bblower_close = DecimalParameter(0.95, 0.995, default=0.993, space='entry', decimals=3, optimize=entry_condition_12_optimize, load=True) entry_condition_12_bblower_low = DecimalParameter(0.95, 0.99, default=0.985, space='entry', decimals=3, optimize=entry_condition_12_optimize, load=True) entry_condition_12_rsi_1h = DecimalParameter(60, 80, default=72.8, space='entry', decimals=1, optimize=entry_condition_12_optimize, load=True) entry_condition_11_optimize = False entry_condition_11_close_1 = DecimalParameter(0.05, 0.15, default=0.1, space='entry', decimals=3, optimize=entry_condition_11_optimize, load=True) entry_condition_11_close_2 = DecimalParameter(0.01, 0.03, default=0.018, space='entry', decimals=3, optimize=entry_condition_11_optimize, load=True) entry_condition_11_rsi = DecimalParameter(49, 53, default=51, space='entry', decimals=2, optimize=entry_condition_11_optimize, load=True) entry_condition_0_optimize = False entry_condition_0_rsi = DecimalParameter(26, 34, default=30, space='entry', decimals=1, optimize=entry_condition_0_optimize, load=True) entry_condition_0_close = DecimalParameter(1, 1.2, default=1.024, space='entry', decimals=3, optimize=entry_condition_0_optimize, load=True) entry_condition_0_rsi_1h = DecimalParameter(66, 76, default=71, space='entry', decimals=1, optimize=entry_condition_0_optimize, load=True) entry_condition_1_rsi_1h = DecimalParameter(63, 75, default=69, space='entry', decimals=1, optimize=False, load=True) entry_condition_10_optimize = False entry_condition_10_rsi = DecimalParameter(35, 45, default=40.5, space='entry', decimals=1, optimize=entry_condition_10_optimize, load=True) entry_condition_10_hist_close = DecimalParameter(0.0001, 0.01, default=0.0012, space='entry', decimals=4, optimize=entry_condition_10_optimize, load=True) custom_stoploss_optimize_1 = False custom_stoploss_optimize_2 = False custom_stoploss_minutes = IntParameter(50, 200, default=50, space='exit', optimize=custom_stoploss_optimize_2, load=True) custom_stoploss_rsi_1h = DecimalParameter(20, 50, default=30, space='exit', decimals=1, optimize=custom_stoploss_optimize_2, load=True) custom_stoploss_current_rates_1 = DecimalParameter(1.001, 1.1, default=1.025, space='exit', decimals=3, optimize=custom_stoploss_optimize_1, load=True) custom_stoploss_current_rates_2 = DecimalParameter(1.001, 1.1, default=1.015, space='exit', decimals=3, optimize=custom_stoploss_optimize_1, load=True) # Sell exit_condition_1_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) exit_condition_2_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) exit_condition_3_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) exit_condition_4_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) exit_condition_5_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) exit_condition_6_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) exit_condition_7_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) exit_condition_8_enable = CategoricalParameter([True, False], default=True, space='exit', optimize=False, load=True) # 48h for pump exit checks exit_pump_threshold_48_1 = DecimalParameter(0.5, 1.2, default=0.9, space='exit', decimals=2, optimize=False, load=True) exit_pump_threshold_48_2 = DecimalParameter(0.4, 0.9, default=0.7, space='exit', decimals=2, optimize=False, load=True) exit_pump_threshold_48_3 = DecimalParameter(0.3, 0.7, default=0.5, space='exit', decimals=2, optimize=False, load=True) # 36h for pump exit checks exit_pump_threshold_36_1 = DecimalParameter(0.5, 0.9, default=0.72, space='exit', decimals=2, optimize=False, load=True) exit_pump_threshold_36_2 = DecimalParameter(3.0, 6.0, default=4.0, space='exit', decimals=2, optimize=False, load=True) exit_pump_threshold_36_3 = DecimalParameter(0.8, 1.6, default=1.0, space='exit', decimals=2, optimize=False, load=True) # 24h for pump exit checks exit_pump_threshold_24_1 = DecimalParameter(0.5, 0.9, default=0.68, space='exit', decimals=2, optimize=False, load=True) exit_pump_threshold_24_2 = DecimalParameter(0.3, 0.6, default=0.62, space='exit', decimals=2, optimize=False, load=True) exit_pump_threshold_24_3 = DecimalParameter(0.2, 0.5, default=0.88, space='exit', decimals=2, optimize=False, load=True) exit_rsi_bb_1 = DecimalParameter(60.0, 80.0, default=79.5, space='exit', decimals=1, optimize=False, load=True) exit_rsi_bb_2 = DecimalParameter(72.0, 90.0, default=81, space='exit', decimals=1, optimize=False, load=True) exit_rsi_main_3 = DecimalParameter(77.0, 90.0, default=82, space='exit', decimals=1, optimize=False, load=True) exit_dual_rsi_rsi_4 = DecimalParameter(72.0, 84.0, default=73.4, space='exit', decimals=1, optimize=False, load=True) exit_dual_rsi_rsi_1h_4 = DecimalParameter(78.0, 92.0, default=79.6, space='exit', decimals=1, optimize=False, load=True) exit_ema_relative_5 = DecimalParameter(0.005, 0.05, default=0.024, space='exit', optimize=False, load=True) exit_rsi_diff_5 = DecimalParameter(0.0, 20.0, default=4.4, space='exit', optimize=False, load=True) exit_rsi_under_6 = DecimalParameter(72.0, 90.0, default=79.0, space='exit', decimals=1, optimize=False, load=True) exit_rsi_1h_7 = DecimalParameter(80.0, 95.0, default=81.7, space='exit', decimals=1, optimize=False, load=True) exit_bb_relative_8 = DecimalParameter(1.05, 1.3, default=1.1, space='exit', decimals=3, optimize=False, load=True) exit_custom_profit_0 = DecimalParameter(0.01, 0.1, default=0.01, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_0 = DecimalParameter(30.0, 40.0, default=34.0, space='exit', decimals=3, optimize=False, load=True) exit_custom_profit_1 = DecimalParameter(0.01, 0.1, default=0.02, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_1 = DecimalParameter(30.0, 50.0, default=35.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_2 = DecimalParameter(0.01, 0.1, default=0.03, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_2 = DecimalParameter(30.0, 50.0, default=37.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_3 = DecimalParameter(0.01, 0.1, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_3 = DecimalParameter(30.0, 50.0, default=42.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_4 = DecimalParameter(0.01, 0.1, default=0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_4 = DecimalParameter(35.0, 50.0, default=43.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_5 = DecimalParameter(0.01, 0.1, default=0.06, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_5 = DecimalParameter(35.0, 50.0, default=45.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_6 = DecimalParameter(0.01, 0.1, default=0.07, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_6 = DecimalParameter(38.0, 55.0, default=48.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_7 = DecimalParameter(0.01, 0.1, default=0.08, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_7 = DecimalParameter(40.0, 58.0, default=54.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_8 = DecimalParameter(0.06, 0.1, default=0.09, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_8 = DecimalParameter(40.0, 50.0, default=55.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_9 = DecimalParameter(0.05, 0.14, default=0.1, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_9 = DecimalParameter(40.0, 60.0, default=54.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_10 = DecimalParameter(0.1, 0.14, default=0.12, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_10 = DecimalParameter(38.0, 50.0, default=42.0, space='exit', decimals=2, optimize=False, load=True) exit_custom_profit_11 = DecimalParameter(0.16, 0.45, default=0.2, space='exit', decimals=3, optimize=False, load=True) exit_custom_rsi_11 = DecimalParameter(28.0, 40.0, default=34.0, space='exit', decimals=2, optimize=False, load=True) # Profit under EMA200 exit_custom_under_profit_0 = DecimalParameter(0.01, 0.4, default=0.01, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_0 = DecimalParameter(28.0, 40.0, default=35.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_1 = DecimalParameter(0.01, 0.1, default=0.02, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_1 = DecimalParameter(36.0, 60.0, default=56.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_2 = DecimalParameter(0.01, 0.1, default=0.03, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_2 = DecimalParameter(46.0, 66.0, default=57.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_3 = DecimalParameter(0.01, 0.1, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_3 = DecimalParameter(50.0, 68.0, default=58.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_4 = DecimalParameter(0.02, 0.1, default=0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_4 = DecimalParameter(50.0, 68.0, default=59.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_5 = DecimalParameter(0.02, 0.1, default=0.06, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_5 = DecimalParameter(46.0, 62.0, default=60.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_6 = DecimalParameter(0.03, 0.1, default=0.07, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_6 = DecimalParameter(44.0, 60.0, default=56.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_7 = DecimalParameter(0.04, 0.1, default=0.08, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_7 = DecimalParameter(46.0, 60.0, default=54.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_8 = DecimalParameter(0.06, 0.12, default=0.09, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_8 = DecimalParameter(40.0, 58.0, default=55.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_9 = DecimalParameter(0.08, 0.14, default=0.1, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_9 = DecimalParameter(40.0, 60.0, default=54.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_10 = DecimalParameter(0.1, 0.16, default=0.12, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_10 = DecimalParameter(30.0, 50.0, default=42.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_under_profit_11 = DecimalParameter(0.16, 0.3, default=0.2, space='exit', decimals=3, optimize=False, load=True) exit_custom_under_rsi_11 = DecimalParameter(24.0, 40.0, default=34.0, space='exit', decimals=1, optimize=False, load=True) # Profit targets for pumped pairs 48h 1 exit_custom_pump_profit_1_1 = DecimalParameter(0.01, 0.03, default=0.01, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_1_1 = DecimalParameter(26.0, 40.0, default=34.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_1_2 = DecimalParameter(0.01, 0.6, default=0.02, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_1_2 = DecimalParameter(36.0, 50.0, default=40.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_1_3 = DecimalParameter(0.02, 0.1, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_1_3 = DecimalParameter(38.0, 50.0, default=42.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_1_4 = DecimalParameter(0.06, 0.12, default=0.1, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_1_4 = DecimalParameter(36.0, 48.0, default=42.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_1_5 = DecimalParameter(0.14, 0.24, default=0.2, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_1_5 = DecimalParameter(20.0, 40.0, default=34.0, space='exit', decimals=1, optimize=False, load=True) # Profit targets for pumped pairs 36h 1 exit_custom_pump_profit_2_1 = DecimalParameter(0.01, 0.03, default=0.01, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_2_1 = DecimalParameter(26.0, 40.0, default=34.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_2_2 = DecimalParameter(0.01, 0.6, default=0.02, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_2_2 = DecimalParameter(36.0, 50.0, default=40.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_2_3 = DecimalParameter(0.02, 0.1, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_2_3 = DecimalParameter(38.0, 50.0, default=40.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_2_4 = DecimalParameter(0.06, 0.12, default=0.1, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_2_4 = DecimalParameter(36.0, 48.0, default=42.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_2_5 = DecimalParameter(0.14, 0.24, default=0.2, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_2_5 = DecimalParameter(20.0, 40.0, default=34.0, space='exit', decimals=1, optimize=False, load=True) # Profit targets for pumped pairs 24h 1 exit_custom_pump_profit_3_1 = DecimalParameter(0.01, 0.03, default=0.01, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_3_1 = DecimalParameter(26.0, 40.0, default=34.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_3_2 = DecimalParameter(0.01, 0.6, default=0.02, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_3_2 = DecimalParameter(34.0, 50.0, default=40.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_3_3 = DecimalParameter(0.02, 0.1, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_3_3 = DecimalParameter(38.0, 50.0, default=40.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_3_4 = DecimalParameter(0.06, 0.12, default=0.1, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_3_4 = DecimalParameter(36.0, 48.0, default=42.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_profit_3_5 = DecimalParameter(0.14, 0.24, default=0.2, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_rsi_3_5 = DecimalParameter(20.0, 40.0, default=34.0, space='exit', decimals=1, optimize=False, load=True) # SMA descending exit_custom_dec_profit_min_1 = DecimalParameter(0.01, 0.1, default=0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_dec_profit_max_1 = DecimalParameter(0.06, 0.16, default=0.12, space='exit', decimals=3, optimize=False, load=True) # Under EMA100 exit_custom_dec_profit_min_2 = DecimalParameter(0.05, 0.12, default=0.07, space='exit', decimals=3, optimize=False, load=True) exit_custom_dec_profit_max_2 = DecimalParameter(0.06, 0.2, default=0.16, space='exit', decimals=3, optimize=False, load=True) # Trail 1 exit_trail_profit_min_1 = DecimalParameter(0.1, 0.2, default=0.16, space='exit', decimals=2, optimize=False, load=True) exit_trail_profit_max_1 = DecimalParameter(0.4, 0.7, default=0.6, space='exit', decimals=2, optimize=False, load=True) exit_trail_down_1 = DecimalParameter(0.01, 0.08, default=0.03, space='exit', decimals=3, optimize=False, load=True) exit_trail_rsi_min_1 = DecimalParameter(16.0, 36.0, default=20.0, space='exit', decimals=1, optimize=False, load=True) exit_trail_rsi_max_1 = DecimalParameter(30.0, 50.0, default=50.0, space='exit', decimals=1, optimize=False, load=True) # Trail 2 exit_trail_profit_min_2 = DecimalParameter(0.08, 0.16, default=0.1, space='exit', decimals=3, optimize=False, load=True) exit_trail_profit_max_2 = DecimalParameter(0.3, 0.5, default=0.4, space='exit', decimals=2, optimize=False, load=True) exit_trail_down_2 = DecimalParameter(0.02, 0.08, default=0.03, space='exit', decimals=3, optimize=False, load=True) exit_trail_rsi_min_2 = DecimalParameter(16.0, 36.0, default=20.0, space='exit', decimals=1, optimize=False, load=True) exit_trail_rsi_max_2 = DecimalParameter(30.0, 50.0, default=50.0, space='exit', decimals=1, optimize=False, load=True) # Trail 3 exit_trail_profit_min_3 = DecimalParameter(0.01, 0.12, default=0.06, space='exit', decimals=3, optimize=False, load=True) exit_trail_profit_max_3 = DecimalParameter(0.1, 0.3, default=0.2, space='exit', decimals=2, optimize=False, load=True) exit_trail_down_3 = DecimalParameter(0.01, 0.06, default=0.05, space='exit', decimals=3, optimize=False, load=True) # Under & near EMA200, accept profit exit_custom_profit_under_rel_1 = DecimalParameter(0.01, 0.04, default=0.024, space='exit', optimize=False, load=True) exit_custom_profit_under_rsi_diff_1 = DecimalParameter(0.0, 20.0, default=4.4, space='exit', optimize=False, load=True) # Under & near EMA200, take the loss exit_custom_stoploss_under_rel_1 = DecimalParameter(0.001, 0.02, default=0.004, space='exit', optimize=False, load=True) exit_custom_stoploss_under_rsi_diff_1 = DecimalParameter(0.0, 20.0, default=10.0, space='exit', optimize=False, load=True) # Long duration/recover stoploss 1 exit_custom_stoploss_long_optimize = False exit_custom_stoploss_long_profit_min_1 = DecimalParameter(-0.1, -0.02, default=-0.08, space='exit', optimize=exit_custom_stoploss_long_optimize, load=True) exit_custom_stoploss_long_profit_max_1 = DecimalParameter(-0.06, -0.01, default=-0.04, space='exit', optimize=exit_custom_stoploss_long_optimize, load=True) exit_custom_stoploss_long_recover_1 = DecimalParameter(0.05, 0.15, default=0.1, space='exit', optimize=exit_custom_stoploss_long_optimize, load=True) exit_custom_stoploss_long_rsi_diff_1 = DecimalParameter(0.0, 20.0, default=4.0, space='exit', optimize=exit_custom_stoploss_long_optimize, load=True) exit_custom_stoploss_2_optimize = False # Long duration/recover stoploss 2 exit_custom_stoploss_long_recover_2 = DecimalParameter(0.03, 0.15, default=0.06, space='exit', optimize=exit_custom_stoploss_2_optimize, load=True) exit_custom_stoploss_long_rsi_diff_2 = DecimalParameter(30.0, 50.0, default=40.0, space='exit', optimize=exit_custom_stoploss_2_optimize, load=True) # Pumped, descending SMA exit_custom_pump_dec_profit_min_1 = DecimalParameter(0.001, 0.04, default=0.005, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_dec_profit_max_1 = DecimalParameter(0.03, 0.08, default=0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_dec_profit_min_2 = DecimalParameter(0.01, 0.08, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_dec_profit_max_2 = DecimalParameter(0.04, 0.1, default=0.06, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_dec_profit_min_3 = DecimalParameter(0.02, 0.1, default=0.06, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_dec_profit_max_3 = DecimalParameter(0.06, 0.12, default=0.09, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_dec_profit_min_4 = DecimalParameter(0.01, 0.05, default=0.02, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_dec_profit_max_4 = DecimalParameter(0.02, 0.1, default=0.04, space='exit', decimals=3, optimize=False, load=True) # Pumped 48h 1, under EMA200 exit_custom_pump_under_profit_min_1 = DecimalParameter(0.02, 0.06, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_under_profit_max_1 = DecimalParameter(0.04, 0.1, default=0.09, space='exit', decimals=3, optimize=False, load=True) # Pumped trail 1 exit_custom_pump_trail_profit_min_1 = DecimalParameter(0.01, 0.12, default=0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_trail_profit_max_1 = DecimalParameter(0.06, 0.16, default=0.07, space='exit', decimals=2, optimize=False, load=True) exit_custom_pump_trail_down_1 = DecimalParameter(0.01, 0.06, default=0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_pump_trail_rsi_min_1 = DecimalParameter(16.0, 36.0, default=20.0, space='exit', decimals=1, optimize=False, load=True) exit_custom_pump_trail_rsi_max_1 = DecimalParameter(30.0, 50.0, default=70.0, space='exit', decimals=1, optimize=False, load=True) # Stoploss, pumped, 48h 1 exit_custom_stoploss_pump_max_profit_1 = DecimalParameter(0.01, 0.04, default=0.025, space='exit', decimals=3, optimize=False, load=True) exit_custom_stoploss_pump_min_1 = DecimalParameter(-0.1, -0.01, default=-0.02, space='exit', decimals=3, optimize=False, load=True) exit_custom_stoploss_pump_max_1 = DecimalParameter(-0.1, -0.01, default=-0.01, space='exit', decimals=3, optimize=False, load=True) exit_custom_stoploss_pump_ma_offset_1 = DecimalParameter(0.7, 0.99, default=0.94, space='exit', decimals=2, optimize=False, load=True) # Stoploss, pumped, 48h 1 exit_custom_stoploss_pump_max_profit_2 = DecimalParameter(0.01, 0.04, default=0.025, space='exit', decimals=3, optimize=False, load=True) exit_custom_stoploss_pump_loss_2 = DecimalParameter(-0.1, -0.01, default=-0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_stoploss_pump_ma_offset_2 = DecimalParameter(0.7, 0.99, default=0.92, space='exit', decimals=2, optimize=False, load=True) # Stoploss, pumped, 36h 3 exit_custom_stoploss_pump_max_profit_3 = DecimalParameter(0.01, 0.04, default=0.008, space='exit', decimals=3, optimize=False, load=True) exit_custom_stoploss_pump_loss_3 = DecimalParameter(-0.16, -0.06, default=-0.12, space='exit', decimals=3, optimize=False, load=True) exit_custom_stoploss_pump_ma_offset_3 = DecimalParameter(0.7, 0.99, default=0.88, space='exit', decimals=2, optimize=False, load=True) # Recover exit_custom_recover_profit_1 = DecimalParameter(0.01, 0.06, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_recover_min_loss_1 = DecimalParameter(0.06, 0.16, default=0.12, space='exit', decimals=3, optimize=False, load=True) exit_custom_recover_profit_min_2 = DecimalParameter(0.01, 0.04, default=0.01, space='exit', decimals=3, optimize=False, load=True) exit_custom_recover_profit_max_2 = DecimalParameter(0.02, 0.08, default=0.05, space='exit', decimals=3, optimize=False, load=True) exit_custom_recover_min_loss_2 = DecimalParameter(0.04, 0.16, default=0.06, space='exit', decimals=3, optimize=False, load=True) exit_custom_recover_rsi_2 = DecimalParameter(32.0, 52.0, default=46.0, space='exit', decimals=1, optimize=False, load=True) # Profit for long duration trades exit_custom_long_profit_min_1 = DecimalParameter(0.01, 0.04, default=0.03, space='exit', decimals=3, optimize=False, load=True) exit_custom_long_profit_max_1 = DecimalParameter(0.02, 0.08, default=0.04, space='exit', decimals=3, optimize=False, load=True) exit_custom_long_duration_min_1 = IntParameter(700, 2000, default=900, space='exit', optimize=False, load=True) ############################################################# def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float, rate: float, time_in_force: str, exit_reason: str, **kwargs) -> bool: return True def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, current_profit: float, **kwargs): dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) last_candle = dataframe.iloc[-1].squeeze() max_profit = (trade.max_rate - trade.open_rate) / trade.open_rate max_loss = (trade.open_rate - trade.min_rate) / trade.min_rate if last_candle is not None: if (current_profit > self.exit_custom_profit_11.value) & (last_candle['rsi'] < self.exit_custom_rsi_11.value): return 'signal_profit_11' if (self.exit_custom_profit_11.value > current_profit > self.exit_custom_profit_10.value) & (last_candle['rsi'] < self.exit_custom_rsi_10.value): return 'signal_profit_10' if (self.exit_custom_profit_10.value > current_profit > self.exit_custom_profit_9.value) & (last_candle['rsi'] < self.exit_custom_rsi_9.value): return 'signal_profit_9' if (self.exit_custom_profit_9.value > current_profit > self.exit_custom_profit_8.value) & (last_candle['rsi'] < self.exit_custom_rsi_8.value): return 'signal_profit_8' if (self.exit_custom_profit_8.value > current_profit > self.exit_custom_profit_7.value) & (last_candle['rsi'] < self.exit_custom_rsi_7.value): return 'signal_profit_7' if (self.exit_custom_profit_7.value > current_profit > self.exit_custom_profit_6.value) & (last_candle['rsi'] < self.exit_custom_rsi_6.value): return 'signal_profit_6' if (self.exit_custom_profit_6.value > current_profit > self.exit_custom_profit_5.value) & (last_candle['rsi'] < self.exit_custom_rsi_5.value): return 'signal_profit_5' elif (self.exit_custom_profit_5.value > current_profit > self.exit_custom_profit_4.value) & (last_candle['rsi'] < self.exit_custom_rsi_4.value): return 'signal_profit_4' elif (self.exit_custom_profit_4.value > current_profit > self.exit_custom_profit_3.value) & (last_candle['rsi'] < self.exit_custom_rsi_3.value): return 'signal_profit_3' elif (self.exit_custom_profit_3.value > current_profit > self.exit_custom_profit_2.value) & (last_candle['rsi'] < self.exit_custom_rsi_2.value): return 'signal_profit_2' elif (self.exit_custom_profit_2.value > current_profit > self.exit_custom_profit_1.value) & (last_candle['rsi'] < self.exit_custom_rsi_1.value): return 'signal_profit_1' elif (self.exit_custom_profit_1.value > current_profit > self.exit_custom_profit_0.value) & (last_candle['rsi'] < self.exit_custom_rsi_0.value): return 'signal_profit_0' # check if close is under EMA200 elif (current_profit > self.exit_custom_under_profit_11.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_11.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_11' elif (self.exit_custom_under_profit_11.value > current_profit > self.exit_custom_under_profit_10.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_10.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_10' elif (self.exit_custom_under_profit_10.value > current_profit > self.exit_custom_under_profit_9.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_9.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_9' elif (self.exit_custom_under_profit_9.value > current_profit > self.exit_custom_under_profit_8.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_8.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_8' elif (self.exit_custom_under_profit_8.value > current_profit > self.exit_custom_under_profit_7.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_7.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_7' elif (self.exit_custom_under_profit_7.value > current_profit > self.exit_custom_under_profit_6.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_6.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_6' elif (self.exit_custom_under_profit_6.value > current_profit > self.exit_custom_under_profit_5.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_5.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_5' elif (self.exit_custom_under_profit_5.value > current_profit > self.exit_custom_under_profit_4.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_4.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_4' elif (self.exit_custom_under_profit_4.value > current_profit > self.exit_custom_under_profit_3.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_3.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_3' elif (self.exit_custom_under_profit_3.value > current_profit > self.exit_custom_under_profit_2.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_2.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_2' elif (self.exit_custom_under_profit_2.value > current_profit > self.exit_custom_under_profit_1.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_1.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_1' elif (self.exit_custom_under_profit_1.value > current_profit > self.exit_custom_under_profit_0.value) & (last_candle['rsi'] < self.exit_custom_under_rsi_0.value) & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_u_0' # check if the pair is "pumped" elif last_candle['exit_pump_48_1_1h'] & (current_profit > self.exit_custom_pump_profit_1_5.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_1_5.value): return 'signal_profit_p_1_5' elif last_candle['exit_pump_48_1_1h'] & (self.exit_custom_pump_profit_1_5.value > current_profit > self.exit_custom_pump_profit_1_4.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_1_4.value): return 'signal_profit_p_1_4' elif last_candle['exit_pump_48_1_1h'] & (self.exit_custom_pump_profit_1_4.value > current_profit > self.exit_custom_pump_profit_1_3.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_1_3.value): return 'signal_profit_p_1_3' elif last_candle['exit_pump_48_1_1h'] & (self.exit_custom_pump_profit_1_3.value > current_profit > self.exit_custom_pump_profit_1_2.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_1_2.value): return 'signal_profit_p_1_2' elif last_candle['exit_pump_48_1_1h'] & (self.exit_custom_pump_profit_1_2.value > current_profit > self.exit_custom_pump_profit_1_1.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_1_1.value): return 'signal_profit_p_1_1' elif last_candle['exit_pump_36_1_1h'] & (current_profit > self.exit_custom_pump_profit_2_5.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_2_5.value): return 'signal_profit_p_2_5' elif last_candle['exit_pump_36_1_1h'] & (self.exit_custom_pump_profit_2_5.value > current_profit > self.exit_custom_pump_profit_2_4.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_2_4.value): return 'signal_profit_p_2_4' elif last_candle['exit_pump_36_1_1h'] & (self.exit_custom_pump_profit_2_4.value > current_profit > self.exit_custom_pump_profit_2_3.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_2_3.value): return 'signal_profit_p_2_3' elif last_candle['exit_pump_36_1_1h'] & (self.exit_custom_pump_profit_2_3.value > current_profit > self.exit_custom_pump_profit_2_2.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_2_2.value): return 'signal_profit_p_2_2' elif last_candle['exit_pump_36_1_1h'] & (self.exit_custom_pump_profit_2_2.value > current_profit > self.exit_custom_pump_profit_2_1.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_2_1.value): return 'signal_profit_p_2_1' elif last_candle['exit_pump_24_1_1h'] & (current_profit > self.exit_custom_pump_profit_3_5.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_3_5.value): return 'signal_profit_p_3_5' elif last_candle['exit_pump_24_1_1h'] & (self.exit_custom_pump_profit_3_5.value > current_profit > self.exit_custom_pump_profit_3_4.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_3_4.value): return 'signal_profit_p_3_4' elif last_candle['exit_pump_24_1_1h'] & (self.exit_custom_pump_profit_3_4.value > current_profit > self.exit_custom_pump_profit_3_3.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_3_3.value): return 'signal_profit_p_3_3' elif last_candle['exit_pump_24_1_1h'] & (self.exit_custom_pump_profit_3_3.value > current_profit > self.exit_custom_pump_profit_3_2.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_3_2.value): return 'signal_profit_p_3_2' elif last_candle['exit_pump_24_1_1h'] & (self.exit_custom_pump_profit_3_2.value > current_profit > self.exit_custom_pump_profit_3_1.value) & (last_candle['rsi'] < self.exit_custom_pump_rsi_3_1.value): return 'signal_profit_p_3_1' elif (self.exit_custom_dec_profit_max_1.value > current_profit > self.exit_custom_dec_profit_min_1.value) & last_candle['sma_200_dec_20']: return 'signal_profit_d_1' elif (self.exit_custom_dec_profit_max_2.value > current_profit > self.exit_custom_dec_profit_min_2.value) & (last_candle['close'] < last_candle['ema_100']): return 'signal_profit_d_2' # Trailing elif (self.exit_trail_profit_max_1.value > current_profit > self.exit_trail_profit_min_1.value) & (self.exit_trail_rsi_min_1.value < last_candle['rsi'] < self.exit_trail_rsi_max_1.value) & (max_profit > current_profit + self.exit_trail_down_1.value): return 'signal_profit_t_1' elif (self.exit_trail_profit_max_2.value > current_profit > self.exit_trail_profit_min_2.value) & (self.exit_trail_rsi_min_2.value < last_candle['rsi'] < self.exit_trail_rsi_max_2.value) & (max_profit > current_profit + self.exit_trail_down_2.value): return 'signal_profit_t_2' elif (self.exit_trail_profit_max_3.value > current_profit > self.exit_trail_profit_min_3.value) & (max_profit > current_profit + self.exit_trail_down_3.value) & last_candle['sma_200_dec_20_1h']: return 'signal_profit_t_3' elif (last_candle['close'] < last_candle['ema_200']) & (current_profit > self.exit_trail_profit_min_3.value) & (current_profit < self.exit_trail_profit_max_3.value) & (max_profit > current_profit + self.exit_trail_down_3.value): return 'signal_profit_u_t_1' # elif (last_candle['exit_pump_48_1_1h']) & (0.06 > current_profit > 0.04) & (last_candle['rsi'] < 54.0) & (current_time - timedelta(minutes=30) < trade.open_date_utc): # return 'signal_profit_p_s_1' elif (current_profit > 0.0) & (last_candle['close'] < last_candle['ema_200']) & ((last_candle['ema_200'] - last_candle['close']) / last_candle['close'] < self.exit_custom_profit_under_rel_1.value) & (last_candle['rsi'] > last_candle['rsi_1h'] + self.exit_custom_profit_under_rsi_diff_1.value): return 'signal_profit_u_e_1' elif (current_profit < -0.0) & (last_candle['close'] < last_candle['ema_200']) & ((last_candle['ema_200'] - last_candle['close']) / last_candle['close'] < self.exit_custom_stoploss_under_rel_1.value) & (last_candle['rsi'] > last_candle['rsi_1h'] + self.exit_custom_stoploss_under_rsi_diff_1.value) & last_candle['sma_200_dec_24'] & (current_time - timedelta(minutes=720) > trade.open_date_utc): return 'signal_stoploss_u_1' elif (self.exit_custom_stoploss_long_profit_min_1.value < current_profit < self.exit_custom_stoploss_long_profit_max_1.value) & (current_profit > -max_loss + self.exit_custom_stoploss_long_recover_1.value) & (last_candle['close'] < last_candle['ema_200']) & (last_candle['rsi'] > last_candle['rsi_1h'] + self.exit_custom_stoploss_long_rsi_diff_1.value) & last_candle['sma_200_dec_24'] & (current_time - timedelta(minutes=1200) > trade.open_date_utc): return 'signal_stoploss_l_r_u_1' elif (current_profit < -0.0) & (current_profit > -max_loss + self.exit_custom_stoploss_long_recover_2.value) & (last_candle['close'] < last_candle['ema_200']) & (last_candle['rsi'] > last_candle['rsi_1h'] + self.exit_custom_stoploss_long_rsi_diff_2.value) & last_candle['sma_200_dec_24'] & (current_time - timedelta(minutes=1200) > trade.open_date_utc): return 'signal_stoploss_l_r_u_2' elif (self.exit_custom_pump_dec_profit_max_1.value > current_profit > self.exit_custom_pump_dec_profit_min_1.value) & last_candle['exit_pump_48_1_1h'] & last_candle['sma_200_dec_20'] & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_p_d_1' elif (self.exit_custom_pump_dec_profit_max_2.value > current_profit > self.exit_custom_pump_dec_profit_min_2.value) & last_candle['exit_pump_48_2_1h'] & last_candle['sma_200_dec_20'] & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_p_d_2' elif (self.exit_custom_pump_dec_profit_max_3.value > current_profit > self.exit_custom_pump_dec_profit_min_3.value) & last_candle['exit_pump_48_3_1h'] & last_candle['sma_200_dec_20'] & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_p_d_3' elif (self.exit_custom_pump_dec_profit_max_4.value > current_profit > self.exit_custom_pump_dec_profit_min_4.value) & last_candle['sma_200_dec_20'] & last_candle['exit_pump_24_2_1h']: return 'signal_profit_p_d_4' # Pumped 48h 1, under EMA200 elif (self.exit_custom_pump_under_profit_max_1.value > current_profit > self.exit_custom_pump_under_profit_min_1.value) & last_candle['exit_pump_48_1_1h'] & (last_candle['close'] < last_candle['ema_200']): return 'signal_profit_p_u_1' # Pumped 36h 2, trail 1 elif last_candle['exit_pump_36_2_1h'] & (self.exit_custom_pump_trail_profit_max_1.value > current_profit > self.exit_custom_pump_trail_profit_min_1.value) & (self.exit_custom_pump_trail_rsi_min_1.value < last_candle['rsi'] < self.exit_custom_pump_trail_rsi_max_1.value) & (max_profit > current_profit + self.exit_custom_pump_trail_down_1.value): return 'signal_profit_p_t_1' # elif (max_profit < self.exit_custom_stoploss_pump_max_profit_1.value) & (self.exit_custom_stoploss_pump_min_1.value < current_profit < self.exit_custom_stoploss_pump_max_1.value) & (last_candle['exit_pump_48_1_1h']) & (last_candle['sma_200_dec_20']) & (last_candle['close'] < (last_candle['ema_200'] * self.exit_custom_stoploss_pump_ma_offset_1.value)): # return 'signal_stoploss_p_1' elif (max_profit < self.exit_custom_stoploss_pump_max_profit_2.value) & (current_profit < self.exit_custom_stoploss_pump_loss_2.value) & last_candle['exit_pump_48_1_1h'] & last_candle['sma_200_dec_20_1h'] & (last_candle['close'] < last_candle['ema_200'] * self.exit_custom_stoploss_pump_ma_offset_2.value): return 'signal_stoploss_p_2' elif (max_profit < self.exit_custom_stoploss_pump_max_profit_3.value) & (current_profit < self.exit_custom_stoploss_pump_loss_3.value) & last_candle['exit_pump_36_3_1h'] & (last_candle['close'] < last_candle['ema_200'] * self.exit_custom_stoploss_pump_ma_offset_3.value): return 'signal_stoploss_p_3' # Recover elif (max_loss > self.exit_custom_recover_min_loss_1.value) & (current_profit > self.exit_custom_recover_profit_1.value): return 'signal_profit_r_1' elif (max_loss > self.exit_custom_recover_min_loss_2.value) & (self.exit_custom_recover_profit_max_2.value > current_profit > self.exit_custom_recover_profit_min_2.value) & (last_candle['rsi'] < self.exit_custom_recover_rsi_2.value): return 'signal_profit_r_2' # Take profit for long duration trades elif (self.exit_custom_long_profit_min_1.value < current_profit < self.exit_custom_long_profit_max_1.value) & (current_time - timedelta(minutes=self.exit_custom_long_duration_min_1.value) > trade.open_date_utc): return 'signal_profit_l_1' return None def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float: # Manage losing trades and open room for better ones. if current_profit > 0: return 0.99 else: trade_time_50 = trade.open_date_utc + timedelta(minutes=int(self.custom_stoploss_minutes.value)) # Trade open more then 60 minutes. For this strategy it's means -> loss # Let's try to minimize the loss if current_time > trade_time_50: try: number_of_candle_shift = int((current_time - trade_time_50).total_seconds() / 300) dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) candle = dataframe.iloc[-number_of_candle_shift].squeeze() # We are at bottom. Wait... if candle['rsi_1h'] < self.custom_stoploss_rsi_1h.value: return 0.99 # Are we still sinking? if candle['close'] > candle['ema_200']: if current_rate * self.custom_stoploss_current_rates_1.value < candle['open']: return 0.01 if current_rate * self.custom_stoploss_current_rates_2.value < candle['open']: return 0.01 except IndexError as error: # Whoops, set stoploss at 10% return 0.1 return 0.99 def range_percent_change(self, dataframe: DataFrame, method, length: int) -> float: """ Rolling Percentage Change Maximum across interval. :param dataframe: DataFrame The original OHLC dataframe :param method: High to Low / Open to Close :param length: int The length to look back """ df = dataframe.copy() if method == 'HL': return (df['high'].rolling(length).max() - df['low'].rolling(length).min()) / df['low'].rolling(length).min() elif method == 'OC': return (df['open'].rolling(length).max() - df['close'].rolling(length).min()) / df['close'].rolling(length).min() else: raise ValueError(f'Method {method} not defined!') def top_percent_change(self, dataframe: DataFrame, length: int) -> float: """ Percentage change of the current close from the range maximum Open price :param dataframe: DataFrame The original OHLC dataframe :param length: int The length to look back """ df = dataframe.copy() if length == 0: return (df['open'] - df['close']) / df['close'] else: return (df['open'].rolling(length).max() - df['close']) / df['close'] def range_maxgap(self, dataframe: DataFrame, length: int) -> float: """ Maximum Price Gap across interval. :param dataframe: DataFrame The original OHLC dataframe :param length: int The length to look back """ df = dataframe.copy() return df['open'].rolling(length).max() - df['close'].rolling(length).min() def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adjustment: float) -> float: """ Maximum Price Gap across interval adjusted. :param dataframe: DataFrame The original OHLC dataframe :param length: int The length to look back :param adjustment: int The adjustment to be applied """ return self.range_maxgap(dataframe, length) / adjustment def range_height(self, dataframe: DataFrame, length: int) -> float: """ Current close distance to range bottom. :param dataframe: DataFrame The original OHLC dataframe :param length: int The length to look back """ df = dataframe.copy() return df['close'] - df['close'].rolling(length).min() def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, pull_thresh: float) -> bool: """ Determine if entry after a pump is safe. :param dataframe: DataFrame The original OHLC dataframe :param length: int The length to look back :param thresh: int Maximum percentage change threshold :param pull_thresh: int Pullback from interval maximum threshold """ df = dataframe.copy() return (df[f'oc_pct_change_{length}'] < thresh) | (self.range_maxgap_adjusted(df, length, pull_thresh) > self.range_height(df, length)) def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_12, thresh_144) -> bool: """ Determine if dip is safe to enter. :param dataframe: DataFrame The original OHLC dataframe :param thresh_0: Threshold value for 0 length top pct change :param thresh_2: Threshold value for 2 length top pct change :param thresh_12: Threshold value for 12 length top pct change :param thresh_144: Threshold value for 144 length top pct change """ return (dataframe['tpct_change_0'] < thresh_0) & (dataframe['tpct_change_2'] < thresh_2) & (dataframe['tpct_change_12'] < thresh_12) & (dataframe['tpct_change_144'] < thresh_144) def informative_pairs(self): pairs = self.dp.current_whitelist() informative_pairs = [(pair, '1h') for pair in pairs] return informative_pairs def informative_1h_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: assert self.dp, 'DataProvider is required for multiple timeframes.' # Get the informative pair informative_1h = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=self.inf_1h) bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) informative_1h['bb_lowerband'] = bollinger['lower'] informative_1h['bb_middleband'] = bollinger['mid'] informative_1h['bb_upperband'] = bollinger['upper'] # EMA informative_1h['ema_12'] = ta.EMA(informative_1h, timeperiod=12) informative_1h['ema_15'] = ta.EMA(informative_1h, timeperiod=15) informative_1h['ema_20'] = ta.EMA(informative_1h, timeperiod=20) informative_1h['ema_26'] = ta.EMA(informative_1h, timeperiod=26) informative_1h['ema_35'] = ta.EMA(informative_1h, timeperiod=35) informative_1h['ema_50'] = ta.EMA(informative_1h, timeperiod=50) informative_1h['ema_100'] = ta.EMA(informative_1h, timeperiod=100) informative_1h['ema_200'] = ta.EMA(informative_1h, timeperiod=200) # SMA informative_1h['sma_200'] = ta.SMA(informative_1h, timeperiod=200) informative_1h['sma_200_dec_20'] = informative_1h['sma_200'] < informative_1h['sma_200'].shift(20) # RSI informative_1h['rsi'] = ta.RSI(informative_1h, timeperiod=14) # BB bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(informative_1h), window=20, stds=2) informative_1h['bb20_2_low'] = bollinger['lower'] informative_1h['bb20_2_mid'] = bollinger['mid'] informative_1h['bb20_2_upp'] = bollinger['upper'] # Chaikin Money Flow informative_1h['cmf'] = chaikin_money_flow(informative_1h, 20) # Pump protections informative_1h['hl_pct_change_48'] = self.range_percent_change(informative_1h, 'HL', 48) informative_1h['hl_pct_change_36'] = self.range_percent_change(informative_1h, 'HL', 36) informative_1h['hl_pct_change_24'] = self.range_percent_change(informative_1h, 'HL', 24) informative_1h['oc_pct_change_48'] = self.range_percent_change(informative_1h, 'OC', 48) informative_1h['oc_pct_change_36'] = self.range_percent_change(informative_1h, 'OC', 36) informative_1h['oc_pct_change_24'] = self.range_percent_change(informative_1h, 'OC', 24) informative_1h['exit_pump_48_1'] = informative_1h['hl_pct_change_48'] > self.exit_pump_threshold_48_1.value informative_1h['exit_pump_48_2'] = informative_1h['hl_pct_change_48'] > self.exit_pump_threshold_48_2.value informative_1h['exit_pump_48_3'] = informative_1h['hl_pct_change_48'] > self.exit_pump_threshold_48_3.value informative_1h['exit_pump_36_1'] = informative_1h['hl_pct_change_36'] > self.exit_pump_threshold_36_1.value informative_1h['exit_pump_36_2'] = informative_1h['hl_pct_change_36'] > self.exit_pump_threshold_36_2.value informative_1h['exit_pump_36_3'] = informative_1h['hl_pct_change_36'] > self.exit_pump_threshold_36_3.value informative_1h['exit_pump_24_1'] = informative_1h['hl_pct_change_24'] > self.exit_pump_threshold_24_1.value informative_1h['exit_pump_24_2'] = informative_1h['hl_pct_change_24'] > self.exit_pump_threshold_24_2.value informative_1h['exit_pump_24_3'] = informative_1h['hl_pct_change_24'] > self.exit_pump_threshold_24_3.value return informative_1h def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) dataframe['bb_lowerband'] = bollinger['lower'] dataframe['bb_middleband'] = bollinger['mid'] dataframe['bb_upperband'] = bollinger['upper'] dataframe['volume_mean_slow'] = dataframe['volume'].rolling(window=48).mean() # MACD dataframe['macd'], dataframe['signal'], dataframe['hist'] = ta.MACD(dataframe['close'], fastperiod=12, slowperiod=26, signalperiod=9) # BB 40 - STD2 bb_40_std2 = qtpylib.bollinger_bands(dataframe['close'], window=40, stds=2) dataframe['bb40_2_low'] = bb_40_std2['lower'] dataframe['bb40_2_mid'] = bb_40_std2['mid'] dataframe['bb40_2_delta'] = (bb_40_std2['mid'] - dataframe['bb40_2_low']).abs() dataframe['closedelta'] = (dataframe['close'] - dataframe['close'].shift()).abs() dataframe['tail'] = (dataframe['close'] - dataframe['bb40_2_low']).abs() # BB 20 - STD2 bb_20_std2 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) dataframe['bb20_2_low'] = bb_20_std2['lower'] dataframe['bb20_2_mid'] = bb_20_std2['mid'] dataframe['bb20_2_upp'] = bb_20_std2['upper'] # EMA 200 dataframe['ema_12'] = ta.EMA(dataframe, timeperiod=12) dataframe['ema_15'] = ta.EMA(dataframe, timeperiod=15) dataframe['ema_20'] = ta.EMA(dataframe, timeperiod=20) dataframe['ema_26'] = ta.EMA(dataframe, timeperiod=26) dataframe['ema_35'] = ta.EMA(dataframe, timeperiod=35) dataframe['ema_50'] = ta.EMA(dataframe, timeperiod=50) dataframe['ema_100'] = ta.EMA(dataframe, timeperiod=100) dataframe['ema_200'] = ta.EMA(dataframe, timeperiod=200) # SMA dataframe['sma_5'] = ta.SMA(dataframe, timeperiod=5) dataframe['sma_30'] = ta.SMA(dataframe, timeperiod=30) dataframe['sma_200'] = ta.SMA(dataframe, timeperiod=200) dataframe['sma_200_dec_20'] = dataframe['sma_200'] < dataframe['sma_200'].shift(20) dataframe['sma_200_dec_24'] = dataframe['sma_200'] < dataframe['sma_200'].shift(24) # MFI dataframe['mfi'] = ta.MFI(dataframe) # EWO dataframe['ewo'] = EWO(dataframe, 50, 200) # RSI dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14) # Chopiness dataframe['chop'] = qtpylib.chopiness(dataframe, 14) # Zero-Lag EMA dataframe['zema'] = zema(dataframe, period=61) # Dip protection dataframe['tpct_change_0'] = self.top_percent_change(dataframe, 0) dataframe['tpct_change_2'] = self.top_percent_change(dataframe, 2) dataframe['tpct_change_12'] = self.top_percent_change(dataframe, 12) dataframe['tpct_change_144'] = self.top_percent_change(dataframe, 144) # Volume dataframe['volume_mean_4'] = dataframe['volume'].rolling(4).mean().shift(1) dataframe['volume_mean_30'] = dataframe['volume'].rolling(30).mean() return dataframe def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # The indicators for the 1h informative timeframe informative_1h = self.informative_1h_indicators(dataframe, metadata) dataframe = merge_informative_pair(dataframe, informative_1h, self.timeframe, self.inf_1h, ffill=True) # The indicators for the normal (5m) timeframe dataframe = self.normal_tf_indicators(dataframe, metadata) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: conditions = [] conditions.append(self.entry_condition_12_enable.value & (dataframe['close'] > dataframe['ema_200']) & (dataframe['close'] > dataframe['ema_200_1h']) & (dataframe['close'] < dataframe['bb_lowerband'] * self.entry_condition_12_bblower_close.value) & (dataframe['low'] < dataframe['bb_lowerband'] * self.entry_condition_12_bblower_low.value) & (dataframe['close'].shift() > dataframe['bb_lowerband']) & (dataframe['rsi_1h'] < self.entry_condition_12_rsi_1h.value) & (dataframe['open'] > dataframe['close']) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['open'] - dataframe['close'] < dataframe['bb_upperband'].shift(2) - dataframe['bb_lowerband'].shift(2)) & (dataframe['volume'] > 0)) # Make sure Volume is not 0 conditions.append(self.entry_condition_11_enable.value & (dataframe['close'] > dataframe['ema_200']) & (dataframe['hist'] > 0) & (dataframe['hist'].shift() > 0) & (dataframe['hist'].shift(2) > 0) & (dataframe['hist'].shift(3) > 0) & (dataframe['hist'].shift(5) > 0) & (dataframe['bb_middleband'] - dataframe['bb_middleband'].shift(5) > dataframe['close'] / 200) & (dataframe['bb_middleband'] - dataframe['bb_middleband'].shift(10) > dataframe['close'] / 100) & (dataframe['bb_upperband'] - dataframe['bb_lowerband'] < dataframe['close'] * self.entry_condition_11_close_1.value) & (dataframe['open'].shift() - dataframe['close'].shift() < dataframe['close'] * self.entry_condition_11_close_2.value) & (dataframe['rsi'] > self.entry_condition_11_rsi.value) & (dataframe['open'] < dataframe['close']) & (dataframe['open'].shift() > dataframe['close'].shift()) & (dataframe['close'] > dataframe['bb_middleband']) & (dataframe['close'].shift() < dataframe['bb_middleband'].shift()) & (dataframe['low'].shift(2) > dataframe['bb_middleband'].shift(2)) & (dataframe['volume'] > 0)) # Make sure Volume is not 0 conditions.append(self.entry_condition_0_enable.value & (dataframe['close'] > dataframe['ema_200']) & (dataframe['rsi'] < self.entry_condition_0_rsi.value) & (dataframe['close'] * self.entry_condition_0_close.value < dataframe['open'].shift(3)) & (dataframe['rsi_1h'] < self.entry_condition_0_rsi_1h.value) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_1_enable.value & (dataframe['close'] > dataframe['ema_200']) & (dataframe['close'] > dataframe['ema_200_1h']) & (dataframe['close'] < dataframe['bb_lowerband'] * self.entry_bb20_close_bblowerband_safe_1.value) & (dataframe['rsi_1h'] < self.entry_condition_1_rsi_1h.value) & (dataframe['open'] > dataframe['close']) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['open'] - dataframe['close'] < dataframe['bb_upperband'].shift(2) - dataframe['bb_lowerband'].shift(2)) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_2_enable.value & (dataframe['close'] > dataframe['ema_200']) & (dataframe['close'] < dataframe['bb_lowerband'] * self.entry_bb20_close_bblowerband_safe_2.value) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['open'] - dataframe['close'] < dataframe['bb_upperband'].shift(2) - dataframe['bb_lowerband'].shift(2)) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_3_enable.value & (dataframe['close'] > dataframe['ema_200_1h']) & (dataframe['close'] < dataframe['bb_lowerband']) & (dataframe['rsi'] < self.entry_rsi_3.value) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_3.value) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_4_enable.value & (dataframe['rsi_1h'] < self.entry_rsi_1h_1.value) & (dataframe['close'] < dataframe['bb_lowerband']) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['volume'] > 0)) # Make sure Volume is not 0 conditions.append(self.entry_condition_5_enable.value & (dataframe['close'] > dataframe['ema_200']) & (dataframe['close'] > dataframe['ema_200_1h']) & (dataframe['ema_26'] > dataframe['ema_12']) & (dataframe['ema_26'] - dataframe['ema_12'] > dataframe['open'] * self.entry_macd_1.value) & (dataframe['ema_26'].shift() - dataframe['ema_12'].shift() > dataframe['open'] / 100) & (dataframe['close'] < dataframe['bb_lowerband']) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_6_enable.value & (dataframe['rsi_1h'] < self.entry_rsi_1h_5.value) & (dataframe['ema_26'] > dataframe['ema_12']) & (dataframe['ema_26'] - dataframe['ema_12'] > dataframe['open'] * self.entry_macd_2.value) & (dataframe['ema_26'].shift() - dataframe['ema_12'].shift() > dataframe['open'] / 100) & (dataframe['close'] < dataframe['bb_lowerband']) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_7_enable.value & (dataframe['rsi_1h'] < self.entry_rsi_1h_2.value) & (dataframe['ema_26'] > dataframe['ema_12']) & (dataframe['ema_26'] - dataframe['ema_12'] > dataframe['open'] * self.entry_macd_1.value) & (dataframe['ema_26'].shift() - dataframe['ema_12'].shift() > dataframe['open'] / 100) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_8_enable.value & (dataframe['rsi_1h'] < self.entry_rsi_1h_3.value) & (dataframe['rsi'] < self.entry_rsi_1.value) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_9_enable.value & (dataframe['rsi_1h'] < self.entry_rsi_1h_4.value) & (dataframe['rsi'] < self.entry_rsi_2.value) & (dataframe['volume'] < dataframe['volume'].shift() * self.entry_volume_drop_1.value) & (dataframe['volume_mean_slow'] > dataframe['volume_mean_slow'].shift(48) * self.entry_volume_pump_1.value) & (dataframe['volume_mean_slow'] * self.entry_volume_pump_1.value < dataframe['volume_mean_slow'].shift(48)) & (dataframe['volume'] > 0)) conditions.append(self.entry_condition_10_enable.value & (dataframe['rsi_1h'] < self.entry_rsi_1h_4.value) & (dataframe['close_1h'] < dataframe['bb_lowerband_1h']) & (dataframe['hist'] > 0) & (dataframe['hist'].shift(2) < 0) & (dataframe['rsi'] < self.entry_condition_10_rsi.value) & (dataframe['hist'] > dataframe['close'] * self.entry_condition_10_hist_close.value) & (dataframe['open'] < dataframe['close']) & (dataframe['volume'] > 0)) if conditions: dataframe.loc[reduce(lambda x, y: x | y, conditions), 'entry'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: conditions = [] conditions.append(self.exit_condition_1_enable.value & (dataframe['rsi'] > self.exit_rsi_bb_1.value) & (dataframe['close'] > dataframe['bb20_2_upp']) & (dataframe['close'].shift(1) > dataframe['bb20_2_upp'].shift(1)) & (dataframe['close'].shift(2) > dataframe['bb20_2_upp'].shift(2)) & (dataframe['close'].shift(3) > dataframe['bb20_2_upp'].shift(3)) & (dataframe['close'].shift(4) > dataframe['bb20_2_upp'].shift(4)) & (dataframe['close'].shift(5) > dataframe['bb20_2_upp'].shift(5)) & (dataframe['volume'] > 0)) conditions.append(self.exit_condition_2_enable.value & (dataframe['rsi'] > self.exit_rsi_bb_2.value) & (dataframe['close'] > dataframe['bb20_2_upp']) & (dataframe['close'].shift(1) > dataframe['bb20_2_upp'].shift(1)) & (dataframe['close'].shift(2) > dataframe['bb20_2_upp'].shift(2)) & (dataframe['volume'] > 0)) conditions.append(self.exit_condition_3_enable.value & (dataframe['rsi'] > self.exit_rsi_main_3.value) & (dataframe['volume'] > 0)) conditions.append(self.exit_condition_4_enable.value & (dataframe['rsi'] > self.exit_dual_rsi_rsi_4.value) & (dataframe['rsi_1h'] > self.exit_dual_rsi_rsi_1h_4.value) & (dataframe['volume'] > 0)) conditions.append(self.exit_condition_6_enable.value & (dataframe['close'] < dataframe['ema_200']) & (dataframe['close'] > dataframe['ema_50']) & (dataframe['rsi'] > self.exit_rsi_under_6.value) & (dataframe['volume'] > 0)) conditions.append(self.exit_condition_7_enable.value & (dataframe['rsi_1h'] > self.exit_rsi_1h_7.value) & qtpylib.crossed_below(dataframe['ema_12'], dataframe['ema_26']) & (dataframe['volume'] > 0)) conditions.append(self.exit_condition_8_enable.value & (dataframe['close'] > dataframe['bb20_2_upp_1h'] * self.exit_bb_relative_8.value) & (dataframe['volume'] > 0)) if conditions: dataframe.loc[reduce(lambda x, y: x | y, conditions), 'exit'] = 1 return dataframe # Elliot Wave Oscillator def EWO(dataframe, sma1_length=5, sma2_length=35): df = dataframe.copy() sma1 = ta.EMA(df, timeperiod=sma1_length) sma2 = ta.EMA(df, timeperiod=sma2_length) smadif = (sma1 - sma2) / df['close'] * 100 return smadif # Chaikin Money Flow def chaikin_money_flow(dataframe, n=20, fillna=False): """Chaikin Money Flow (CMF) It measures the amount of Money Flow Volume over a specific period. http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:chaikin_money_flow_cmf Args: dataframe(pandas.Dataframe): dataframe containing ohlcv n(int): n period. fillna(bool): if True, fill nan values. Returns: pandas.Series: New feature generated. """ df = dataframe.copy() mfv = (df['close'] - df['low'] - (df['high'] - df['close'])) / (df['high'] - df['low']) mfv = mfv.fillna(0.0) # float division by zero mfv *= df['volume'] cmf = mfv.rolling(n, min_periods=0).sum() / df['volume'].rolling(n, min_periods=0).sum() if fillna: cmf = cmf.replace([np.inf, -np.inf], np.nan).fillna(0) return Series(cmf, name='cmf')