Timeframe
5m
Direction
Long Only
Stoploss
-23.0%
Trailing Stop
No
ROI
0m: 1000.0%
Interface Version
2
Startup Candles
400
Indicators
3
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
from datetime import datetime
import talib.abstract as ta
from pandas import DataFrame
from freqtrade.persistence import Trade
from freqtrade.strategy import DecimalParameter, IntParameter
from freqtrade.strategy.interface import IStrategy
# Author @Jooopieeert#0239
class SMA1Sell(IStrategy):
INTERFACE_VERSION = 2
buy_params = {
"base_nb_candles_buy": 18,
"low_offset": 0.968,
}
sell_params = {
"base_nb_candles_sell": 26,
"high_offset": 0.985,
}
base_nb_candles_buy = IntParameter(16, 60, default=buy_params['base_nb_candles_buy'], space='buy', optimize=True)
base_nb_candles_sell = IntParameter(16, 60, default=sell_params['base_nb_candles_sell'], space='sell', optimize=False)
low_offset = DecimalParameter(0.8, 0.99, default=buy_params['low_offset'], space='buy', optimize=True)
high_offset = DecimalParameter(0.8, 1.1, default=sell_params['high_offset'], space='sell', optimize=False)
timeframe = '5m'
stoploss = -0.23
minimal_roi = {"0": 10,}
trailing_stop = False
trailing_only_offset_is_reached = True
trailing_stop_positive = 0.003
trailing_stop_positive_offset = 0.018
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
process_only_new_candles = True
startup_candle_count = 400
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['ema_50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema_200'] = ta.EMA(dataframe, timeperiod=200)
dataframe['rsi_exit'] = ta.RSI(dataframe, timeperiod=2)
if not self.config['runmode'].value == 'hyperopt':
dataframe['ma_offset_buy'] = ta.SMA(dataframe, int(self.base_nb_candles_buy.value)) * self.low_offset.value
dataframe['ma_offset_sell'] = ta.EMA(dataframe, int(self.base_nb_candles_sell.value)) * self.high_offset.value
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
if self.config['runmode'].value == 'hyperopt':
dataframe['ma_offset_buy'] = ta.SMA(dataframe, int(self.base_nb_candles_buy.value)) * self.low_offset.value
dataframe.loc[
(
(dataframe['ema_50'] > dataframe['ema_200']) &
(dataframe['close'] > dataframe['ema_200']) &
(dataframe['close'] < dataframe['ma_offset_buy']) &
(dataframe['volume'] > 0)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
if self.config['runmode'].value == 'hyperopt':
dataframe['ma_offset_sell'] = ta.EMA(dataframe, int(self.base_nb_candles_sell.value)) * self.high_offset.value
dataframe.loc[
(
(dataframe['close'] > dataframe['ma_offset_sell']) &
(
(dataframe['open'] < dataframe['open'].shift(1)) |
(dataframe['rsi_exit'] < 50) |
(dataframe['rsi_exit'] < dataframe['rsi_exit'].shift(1))
) &
(dataframe['volume'] > 0)
),
'sell'] = 1
return dataframe