trading strategy based on the concept explained at https://www.youtube.com/watch?v=mmAWVmKN4J0 author@: Gert Wohlgemuth
Timeframe
N/A
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
trading strategy based on the concept explained at https://www.youtube.com/watch?v=mmAWVmKN4J0 author@: Gert Wohlgemuth
freqtrade/freqtrade-strategies
Strategy 005 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
freqtrade/freqtrade-strategies
author@: Gert Wohlgemuth
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from hyperopt import hp
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
"""
# 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 ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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'])
),
'sell'] = 1
return dataframe