trading strategy based on the concept explained at https://www.youtube.com/watch?v=mmAWVmKN4J0 author@: Gert Wohlgemuth idea: uptrend definition: MACD above 0 line AND above MACD signal downtrend definition: MACD below 0 line and below MACD signal sell definition: MACD below MACD signal it's basically a very simple MACD based strategy and we ignore the definition of the entry and exit points in this case, since the trading bot, will take of this already
Timeframe
5m
Direction
Long Only
Stoploss
-30.0%
Trailing Stop
No
ROI
0m: 5.0%, 20m: 4.0%, 30m: 3.0%, 60m: 1.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
1
freqtrade/freqtrade-strategies
# --- Do not remove these libs ---
from freqtrade.strategy import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class ASDTSRockwellTrading(IStrategy):
"""
trading strategy based on the concept explained at https://www.youtube.com/watch?v=mmAWVmKN4J0
author@: Gert Wohlgemuth
idea:
uptrend definition:
MACD above 0 line AND above MACD signal
downtrend definition:
MACD below 0 line and below MACD signal
sell definition:
MACD below MACD signal
it's basically a very simple MACD based strategy and we ignore the definition of the entry and exit points in this case, since the trading bot, will take of this already
"""
INTERFACE_VERSION: int = 3
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"60": 0.01,
"30": 0.03,
"20": 0.04,
"0": 0.05
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.3
# Optimal timeframe for the strategy
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['macd'] > 0) &
(dataframe['macd'] > dataframe['macdsignal'])
),
'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['macd'] < dataframe['macdsignal'])
),
'exit_long'] = 1
return dataframe