EnsembleStrategyV1

from freqtrade.strategy import IStrategy, IntParameter, DecimalParameter
import logging
from pandas import DataFrame
from freqtrade.resolvers import StrategyResolver
from itertools import combinations
from functools import reduce
logger = logging.getLogger(__name__)
'\nHyperoptimizedd using OnlyProfitHyperOptLoss\n======================================================= SELL REASON STATS ========================================================\n|        Sell Reason |   Sells |   Win  Draws  Loss  Win% |   Avg Profit % |   Cum Profit % |   Tot Profit USDT |   Tot Profit % |\n|--------------------+---------+--------------------------+----------------+----------------+-------------------+----------------|\n|        exit_signal |     507 |    333     0   174  65.7 |           0.13 |          67.95 |           253.527 |          16.99 |\n| trailing_stop_loss |     103 |    103     0     0   100 |           4.88 |         502.33 |          2764.21  |         125.58 |\n|                roi |      37 |     35     2     0   100 |           7.93 |         293.51 |          1247.71  |          73.38 |\n|          stop_loss |      12 |      0     0    12     0 |         -20.46 |        -245.51 |         -1139.88  |         -61.38 |\n====================================================== LEFT OPEN TRADES REPORT ======================================================\n|   Pair |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit USDT |   Tot Profit % |   Avg Duration |   Win  Draw  Loss  Win% |\n|--------+--------+----------------+----------------+-------------------+----------------+----------------+-------------------------|\n|  TOTAL |      0 |           0.00 |           0.00 |             0.000 |           0.00 |           0:00 |     0     0     0     0 |\n=============== SUMMARY METRICS ===============\n| Metric                | Value               |\n|-----------------------+---------------------|\n| Backtesting from      | 2021-05-01 00:00:00 |\n| Backtesting to        | 2021-05-31 15:30:00 |\n| Max open trades       | 4                   |\n|                       |                     |\n| Total trades          | 659                 |\n| Starting balance      | 1000.000 USDT       |\n| Final balance         | 4125.571 USDT       |\n| Absolute profit       | 3125.571 USDT       |\n| Total profit %        | 312.56%             |\n| Trades per day        | 21.97               |\n| Avg. stake amount     | 533.922 USDT        |\n| Total trade volume    | 351854.681 USDT     |\n|                       |                     |\n| Best Pair             | MATIC/USDT 180.8%   |\n| Worst Pair            | STORJ/USDT -20.27%  |\n| Best trade            | DOT/USDT 24.18%     |\n| Worst trade           | ZEC/USDT -20.46%    |\n| Best day              | 793.247 USDT        |\n| Worst day             | -198.590 USDT       |\n| Days win/draw/lose    | 26 / 0 / 5          |\n| Avg. Duration Winners | 0:41:00             |\n| Avg. Duration Loser   | 1:52:00             |\n| Zero Duration Trades  | 3.64% (24)          |\n| Rejected Buy signals  | 45400               |\n|                       |                     |\n| Min balance           | 1011.385 USDT       |\n| Max balance           | 4125.571 USDT       |\n| Drawdown              | 186.4%              |\n| Drawdown              | 824.540 USDT        |\n| Drawdown high         | 1100.474 USDT       |\n| Drawdown low          | 275.934 USDT        |\n| Drawdown Start        | 2021-05-19 01:20:00 |\n| Drawdown End          | 2021-05-19 12:50:00 |\n| Market change         | -28.01%             |\n===============================================\n'
# DO NOT MODIFY THE STRATEGY LIST
# You'll need to run hyperopt to find the best strategy combination for entry/exit.
# Also, make sure you have all strategies listed here in user_data/strategies
STRATEGIES = ['CombinedBinHAndCluc', 'CombinedBinHAndClucV2', 'CombinedBinHAndClucV5', 'CombinedBinHAndClucV6H', 'CombinedBinHAndClucV7', 'CombinedBinHAndClucV8', 'CombinedBinHAndClucV8Hyper', 'SMAOffset', 'SMAOffsetV2', 'NostalgiaForInfinityV1', 'NostalgiaForInfinityV2']
STRAT_COMBINATIONS = reduce(lambda x, y: list(combinations(STRATEGIES, y)) + x, range(len(STRATEGIES) + 1), [])

class EnsembleStrategyV1(IStrategy):
    INTERFACE_VERSION = 3
    loaded_strategies = {}
    entry_mean_threshold = DecimalParameter(0.0, 1, default=0.5, load=True)
    exit_mean_threshold = DecimalParameter(0.0, 1, default=0.5, load=True)
    entry_strategies = IntParameter(0, len(STRAT_COMBINATIONS), default=0, load=True)
    exit_strategies = IntParameter(0, len(STRAT_COMBINATIONS), default=0, load=True)
    # Buy hyperspace params:
    entry_params = {'entry_mean_threshold': 0.124, 'entry_strategies': 1440}
    # Sell hyperspace params:
    exit_params = {'exit_mean_threshold': 0.791, 'exit_strategies': 1654}
    # ROI table:
    minimal_roi = {'0': 0.242, '28': 0.046, '68': 0.035, '137': 0}
    # Stoploss:
    stoploss = -0.203
    # Trailing stop:
    trailing_stop = True
    trailing_stop_positive = 0.01
    trailing_stop_positive_offset = 0.041
    trailing_only_offset_is_reached = True
    process_only_new_candles = True
    informative_timeframe = '1h'

    def __init__(self, config: dict) -> None:
        super().__init__(config)
        logger.info(f'Buy stratrategies: {STRAT_COMBINATIONS[self.entry_strategies.value]}')
        logger.info(f'Sell stratrategies: {STRAT_COMBINATIONS[self.exit_strategies.value]}')

    def informative_pairs(self):
        pairs = self.dp.current_whitelist()
        informative_pairs = [(pair, self.informative_timeframe) for pair in pairs]
        return informative_pairs

    def get_strategy(self, strategy_name):
        cached_strategy = self.loaded_strategies.get(strategy_name)
        if cached_strategy:
            cached_strategy.dp = self.dp
            return cached_strategy
        config = self.config
        config['strategy'] = strategy_name
        strategy = StrategyResolver.load_strategy(config)
        strategy.dp = self.dp
        self.loaded_strategies[strategy_name] = strategy
        return strategy

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        strategies = STRAT_COMBINATIONS[self.entry_strategies.value]
        for strategy_name in strategies:
            strategy = self.get_strategy(strategy_name)
            strategy_indicators = strategy.advise_indicators(dataframe, metadata)
            dataframe[f'strat_entry_signal_{strategy_name}'] = strategy.advise_entry(strategy_indicators, metadata)['enter_long']
        dataframe['enter_long'] = (dataframe.filter(like='strat_entry_signal_').mean(axis=1) > self.entry_mean_threshold.value).astype(int)
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        strategies = STRAT_COMBINATIONS[self.exit_strategies.value]
        for strategy_name in strategies:
            strategy = self.get_strategy(strategy_name)
            strategy_indicators = strategy.advise_indicators(dataframe, metadata)
            dataframe[f'strat_exit_signal_{strategy_name}'] = strategy.advise_exit(strategy_indicators, metadata)['exit_long']
        dataframe['exit_long'] = (dataframe.filter(like='strat_exit_signal_').mean(axis=1) > self.exit_mean_threshold.value).astype(int)
        return dataframe