Timeframe
4h
Direction
Long Only
Stoploss
-32.3%
Trailing Stop
No
ROI
0m: 4.0%, 20m: 5.0%, 30m: 5.0%, 60m: 10.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
1
# Freqtrade_backtest_validation_freqtrade1.py
# This script is 1 of a pair the other being freqtrade_backtest_validation_tradingview1
# These should be executed on their respective platforms for the same coin/period/resolution
# The purpose is to test Freqtrade backtest provides like results to a known industry platform.
#
# --- Do not remove these libs ---
#
#
#
# - EDIT: "Maybe the sucess of a trading system is part of strategy and also a good config.son too!"
#
#
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy
class Chispei(IStrategy):
# Minimal ROI designed for the strategy.
minimal_roi = {
"5127": 0,
"1836": 0.676,
"2599": 0.079,
"120": 0.10,
"60": 0.10,
"30": 0.05,
"20": 0.05,
"0": 0.04
}
stoploss = -0.32336
timeframe = '4h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# SMA - Simple Moving Average
dataframe['fastMA'] = ta.SMA(dataframe, timeperiod=13)
dataframe['slowMA'] = ta.SMA(dataframe, timeperiod=25)
dataframe['mom'] = ta.MOM(dataframe, timeperiod=21)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['mom'] < 15) &
(dataframe['fastMA'] > dataframe['slowMA'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['mom'] < 80) &
(dataframe['fastMA'] < dataframe['slowMA'])
),
'sell'] = 1
return dataframe