134 lines
4.0 KiB
Python
134 lines
4.0 KiB
Python
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
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# --- Do not remove these libs ---
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import numpy # noqa
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import pandas # noqa
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from pandas import DataFrame
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from freqtrade.strategy.interface import IStrategy
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# --------------------------------
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# Add your lib to import here
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import talib.abstract as ta
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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class BBRSI(IStrategy):
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"""
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You must keep:
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- the lib in the section "Do not remove these libs"
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- the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend,
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populate_sell_trend, hyperopt_space, buy_strategy_generator
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"""
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# Strategy interface version - allow new iterations of the strategy interface.
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INTERFACE_VERSION = 2
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# Minimal ROI designed for the strategy.
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# Will override config file.
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minimal_roi = {
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"0": 100
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}
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# Optimal stoploss designed for the strategy.
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# Will override config file.
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stoploss = -0.99
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# Trailing stoploss
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trailing_stop = False
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# trailing_only_offset_is_reached = False
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# trailing_stop_positive = 0.01
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# trailing_stop_positive_offset = 0.0 # Disabled / not configured
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# Optimal timeframe for the strategy.
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timeframe = '1h'
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# Run "populate_indicators()" only for new candle.
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process_only_new_candles = False
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# These values can be overridden in the "ask_strategy" section in the config.
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use_sell_signal = True
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sell_profit_only = False
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ignore_roi_if_buy_signal = False
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# Number of candles the strategy requires before producing valid signals
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startup_candle_count: int = 20
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# Optional order type mapping.
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order_types = {
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'buy': 'limit',
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'sell': 'limit',
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'stoploss': 'market',
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'stoploss_on_exchange': False
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}
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# Optional order time in force.
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order_time_in_force = {
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'buy': 'gtc',
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'sell': 'gtc'
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}
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plot_config = {
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# Main plot indicators (Moving averages, ...)
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'main_plot': {
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'tema': {},
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'sar': {'color': 'white'},
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},
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'subplots': {
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# Subplots - each dict defines one additional plot
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"MACD": {
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'macd': {'color': 'blue'},
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'macdsignal': {'color': 'orange'},
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},
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"RSI": {
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'rsi': {'color': 'red'},
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}
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}
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}
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def informative_pairs(self):
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"""
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Define additional, informative pair/interval combinations to be cached from the exchange.
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These pair/interval combinations are non-tradeable, unless they are part
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of the whitelist as well.
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For more information, please consult the documentation
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:return: List of tuples in the format (pair, interval)
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Sample: return [("ETH/USDT", "5m"),
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("BTC/USDT", "15m"),
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]
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"""
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return []
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# RSI
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dataframe['rsi'] = ta.RSI(dataframe)
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# Bollinger Bands
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bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
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dataframe['bb_lowerband'] = bollinger['lower']
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dataframe['bb_middleband'] = bollinger['mid']
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dataframe['bb_upperband'] = bollinger['upper']
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return dataframe
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def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe.loc[
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(
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(dataframe['rsi'] > 30) & # RSI above 30
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(dataframe['close'] < dataframe['bb_lowerband']) # close price under low bb
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),
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'buy'] = 1
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return dataframe
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def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe.loc[
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(
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(dataframe['close'] > dataframe['bb_middleband']) # close price above the middle bb
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),
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'sell'] = 1
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return dataframe
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