Timeframe
15m
Direction
Long Only
Stoploss
-20.0%
Trailing Stop
No
ROI
0m: 50.0%
Interface Version
3
Startup Candles
N/A
Indicators
1
freqtrade/freqtrade-strategies
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
# --- 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 EMAVolume(IStrategy):
INTERFACE_VERSION = 3
"\n\n author@: Gert Wohlgemuth\n\n idea:\n entrys and exits on crossovers - doesn't really perfom that well and its just a proof of concept\n "
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {'0': 0.5}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.2
# Optimal ticker interval for the strategy
timeframe = '15m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['ema13'] = ta.EMA(dataframe, timeperiod=13)
dataframe['ema34'] = ta.EMA(dataframe, timeperiod=34)
dataframe['ema7'] = ta.EMA(dataframe, timeperiod=7)
dataframe['ema21'] = ta.EMA(dataframe, timeperiod=21)
dataframe['volume_mean'] = dataframe['volume'].rolling(window=10).mean()
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema200'] = ta.EMA(dataframe, timeperiod=200)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the entry signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with entry column
"""
dataframe.loc[qtpylib.crossed_above(dataframe['ema13'], dataframe['ema34']) & (dataframe['volume'] > dataframe['volume'].rolling(window=10).mean()), 'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the exit signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with entry column
"""
dataframe.loc[qtpylib.crossed_below(dataframe['ema13'], dataframe['ema34']), 'exit_long'] = 1
return dataframe