Timeframe
5m
Direction
Long Only
Stoploss
-4.0%
Trailing Stop
No
ROI
0m: 2.0%
Interface Version
3
Startup Candles
N/A
Indicators
3
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np
import pandas as pd
from pandas import DataFrame
from datetime import datetime
from typing import Optional, Union
from functools import reduce
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IntParameter, IStrategy, merge_informative_pair)
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import pandas_ta as pta
from technical import qtpylib
class zemastoch1_1(IStrategy):
INTERFACE_VERSION = 3
timeframe = '5m'
minimal_roi = {
"0":0.02 #0.5 5 %
}
buy_params={
"fastd_period":5,
"fastk_period":3,
"stoch_period":14,
"ema_long_period":50,
"ema_fast_period":20
}
stoploss = -0.04 #1 ta 10%
trailing_stop = False
use_exit_signal = False
exit_profit_only = False
ignore_roi_if_entry_signal = False
ema_fast_period = IntParameter(5, 50, default= 20,space ='buy')
ema_long_period = IntParameter(10, 100, default=50,space ='buy')
fastk_period = IntParameter(2, 7, default=int(buy_params['fastk_period']),space="buy")
fastd_period =IntParameter(2, 5,default=int(buy_params['fastd_period']),space="buy" )
lenght_period = IntParameter(7, 25, default= int(buy_params['stoch_period']),space="buy" )
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
for val in self.ema_fast_period.range:
dataframe[f"ema_fast_{val}"] = ta.EMA(dataframe, timeperiod=val)
for val in self.ema_long_period.range:
dataframe[f"ema_long_{val}"] = ta.EMA(dataframe, timeperiod=val)
#------------------------------------------------------------------------------------------
for val in self.lenght_period.range:
for val_1 in self.fastk_period.range:
for val_2 in self.fastd_period.range:
dataframe[f'fastk_{val}_{val_1}_{val_2}'] = ta.STOCHRSI(dataframe,timeperiod = val,fastk_period=val_1,
fastd_period=val_2, fastd_matype=0)['fastk']
dataframe[f'fastd_{val}_{val_1}_{val_2}'] = ta.STOCHRSI(dataframe,timeperiod = val,fastk_period=val_1,
fastd_period=val_2, fastd_matype=0)['fastd']
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# enter Long
conditions_long = []
conditions_short = []
conditions_long.append(qtpylib.crossed_below(
dataframe[f'ema_fast_{self.ema_fast_period.value}'],
dataframe[f'ema_long_{self.ema_long_period.value}'],
))
conditions_long.append(
dataframe[f'fastd_{self.lenght_period.value}_{self.fastk_period.value}_{self.fastd_period.value}']
< dataframe[f'fastk_{self.lenght_period.value}_{self.fastk_period.value}_{self.fastd_period.value}']
)
# enter Short
conditions_short.append(qtpylib.crossed_above(
dataframe[f'ema_fast_{self.ema_fast_period.value}'],
dataframe[f'ema_long_{self.ema_long_period.value}'],
))
conditions_short.append(
dataframe[f'fastd_{self.lenght_period.value}_{self.fastk_period.value}_{self.fastd_period.value}']
> dataframe[f'fastk_{self.lenght_period.value}_{self.fastk_period.value}_{self.fastd_period.value}']
)
dataframe.loc[
reduce(lambda x, y: x & y, conditions_long),
"enter_long",
] = 1
dataframe.loc[
reduce(lambda x, y: x & y, conditions_short),
"enter_short",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
#(qtpylib.crossed_below(dataframe['close'],dataframe['ema50']))
#(qtpylib.crossed_above(dataframe['ema20'],dataframe['ema50']))
),
'exit_long'] = 1
dataframe.loc[
(
#(qtpylib.crossed_above(dataframe['close'],dataframe['ema50']))
#(qtpylib.crossed_below(dataframe['ema20'],dataframe['ema50']))
),
['exit_short']] = 1
return dataframe