author@: Gert Wohlgemuth
Timeframe
4h
Direction
Long Only
Stoploss
-25.0%
Trailing Stop
No
ROI
0m: 10000.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
2
freqtrade/freqtrade-strategies
# --- Do not remove these libs ---
from freqtrade.strategy.interface 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 WaveTrendStra(IStrategy):
"""
author@: Gert Wohlgemuth
just a skeleton
"""
# Minimal ROI designed for the strategy.
# adjust based on market conditions. We would recommend to keep it low for quick turn arounds
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 100 #disable roi
}
# Optimal stoploss designed for the strategy
stoploss = -0.25
# Optimal timeframe for the strategy
timeframe = '4h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
ap = (dataframe["high"] + dataframe["low"] + dataframe["close"]) / 3
esa = ta.EMA(ap, 10)
d = ta.EMA(abs(ap - esa), 10)
ci = (ap - esa) / (0.015 * d)
tci = ta.EMA(ci, 21)
dataframe["wt1"] = tci
dataframe["wt2"] = ta.SMA(dataframe["wt1"], 4)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(qtpylib.crossed_above(dataframe["wt1"], dataframe["wt2"]))
,'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(qtpylib.crossed_below(dataframe['wt1'], dataframe['wt2']))
,'sell'] = 1
return dataframe