Timeframe
1d
Direction
Long Only
Stoploss
-99.0%
Trailing Stop
Yes
ROI
0m: 23.7%, 4195m: 17.0%, 7191m: 5.3%, 14695m: 0.0%
Interface Version
2
Startup Candles
N/A
Indicators
4
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
import copy
import logging
import pathlib
import rapidjson
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
import talib.abstract as ta
import pandas as pd
import pandas_ta as pta
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy import merge_informative_pair, timeframe_to_minutes
from freqtrade.exchange import timeframe_to_prev_date
from pandas import DataFrame, Series, concat
from functools import reduce
import math
from typing import Dict
from freqtrade.persistence import Trade
from datetime import datetime, timedelta
from technical.util import resample_to_interval, resampled_merge
from technical.indicators import RMI, zema, VIDYA, ichimoku
import time
import warnings
# Custom imports to fetch API data
import requests
import json
class INSIDEUP(IStrategy):
INTERFACE_VERSION = 2
# ROI table:
minimal_roi = {
"0": 0.237,
"4195": 0.17,
"7191": 0.053,
"14695": 0
}
# Stoploss:
stoploss = -0.99 # value loaded from strategy
# Trailing stop:
trailing_stop = True # value loaded from strategy
trailing_stop_positive = 0.011 # value loaded from strategy
trailing_stop_positive_offset = 0.029 # value loaded from strategy
trailing_only_offset_is_reached = True # value loaded from strategy
# Optimal timeframe for the strategy.
timeframe = '1d'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = True
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = False
sell_profit_only = False
ignore_roi_if_buy_signal = False
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Inputs:
# # prices: ['open', 'high', 'low', 'close']
# # Three Inside Up/Down: values [0, -100, 100]
dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [-100, 0, 100]
# # MORNINGDOJISTAR: values [0, 100]
dataframe['CDLMORNINGDOJISTAR'] = ta.CDLMORNINGDOJISTAR(dataframe) # values [0, 100]
# # Piercing Line: values [0, 100]
dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
# # Three Black Crows: values [-100, 0, 100]
dataframe['CDL3BLACKCROWS'] = ta.CDL3BLACKCROWS(dataframe) # values [-100, 0, 100]
# RSI
dataframe['rsi_14'] = ta.RSI(dataframe, timeperiod=14)
# ADX
dataframe['adx'] = ta.ADX(dataframe)
dataframe['slowadx'] = ta.ADX(dataframe, 35)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dateTime = datetime.now()
dataframe.loc[
# Check for downtrend movement
(
(dataframe['close'] < dataframe['close'].shift(2)) |
(dataframe['rsi_14'] < 50)
) &
(
(dataframe['adx'] > 13.0)
) &
# Check for patterns
(
# the user should consider that a three inside up is significant
#when it appears in a downtrend
(dataframe['CDL3INSIDE'] >= 0).any() # Bullish
),
['buy', 'buy_tag']] = (1, 'buy_3_inside')
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
no sell signal
"""
dataframe.loc[:, 'sell'] = 0
return dataframe