Timeframe
1d
Direction
Long Only
Stoploss
-99.0%
Trailing Stop
No
ROI
0m: 9999999900.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
1
freqtrade/freqtrade-strategies
Sample strategy implementing Informative Pairs - compares stake_currency with USDT. Not performing very well - but should serve as an example how to use a referential pair against USDT. author@: xmatthias github@: https://github.com/freqtrade/freqtrade-strategies
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
freqtrade/freqtrade-strategies
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class Babico_SMA5xBBmid(IStrategy):
minimal_roi = {
"0": 99999999
}
stoploss = -0.99
# Trailing stoploss (not used)
trailing_stop = False
trailing_only_offset_is_reached = True
trailing_stop_positive = 0.01
trailing_stop_positive_offset = 0.03
use_sell_signal = True
sell_profit_only = True
process_only_new_candles = True
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'trailing_stop_loss': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False
}
# Optimal timeframe for the strategy
timeframe = '1d'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
bb = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_low'] = bb['lower']
dataframe['bb_mid'] = bb['mid']
dataframe['bb_upp'] = bb['upper']
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
qtpylib.crossed_above(dataframe['ema5'], dataframe['bb_mid'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
qtpylib.crossed_above(dataframe['bb_mid'], dataframe['ema5'])
),
'sell'] = 1
return dataframe