Timeframe
15m
Direction
Long Only
Stoploss
-29.4%
Trailing Stop
No
ROI
0m: 7.8%, 40m: 6.2%, 99m: 3.9%, 218m: 0.0%
Interface Version
N/A
Startup Candles
500
Indicators
2
freqtrade/freqtrade-strategies
freqtrade/freqtrade-strategies
freqtrade/freqtrade-strategies
This strategy uses custom_stoploss() to enforce a fixed risk/reward ratio by first calculating a dynamic initial stoploss via ATR - last negative peak
freqtrade/freqtrade-strategies
# --- Do not remove these libs ---
from freqtrade.strategy import IStrategy, merge_informative_pair, DecimalParameter, IntParameter
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
from functools import reduce
# --------------------------------
import pandas as pd
import numpy as np
import technical.indicators as ftt
from freqtrade.exchange import timeframe_to_minutes
import logging
logger = logging.getLogger(__name__)
# Obelisk_Ichimoku_ZEMA v1 - 2021-05-20
#
# EXPERIMENTAL
#
# RUN AT YOUR OWN RISK
#
# by Obelisk
# https://github.com/brookmiles/
def ssl_atr(dataframe, length=7):
df = dataframe.copy()
df['smaHigh'] = df['high'].rolling(length).mean() + df['atr']
df['smaLow'] = df['low'].rolling(length).mean() - df['atr']
df['hlv'] = np.where(df['close'] > df['smaHigh'], 1,
np.where(df['close'] < df['smaLow'], -1, np.NAN))
df['hlv'] = df['hlv'].ffill()
df['sslDown'] = np.where(df['hlv'] < 0, df['smaHigh'], df['smaLow'])
df['sslUp'] = np.where(df['hlv'] < 0, df['smaLow'], df['smaHigh'])
return df['sslDown'], df['sslUp']
class IchimokuV1(IStrategy):
# Optimal timeframe for the strategy
timeframe = '15m'
# generate signals from the 1h timeframe
informative_timeframe = '1h'
# WARNING: ichimoku is a long indicator, if you remove or use a
# shorter startup_candle_count your backtest results will be unreliable
startup_candle_count = 500
# NOTE: this strat only uses candle information, so processing between
# new candles is a waste of resources as nothing will change
process_only_new_candles = True
# ROI table:
minimal_roi = {
"0": 0.078,
"40": 0.062,
"99": 0.039,
"218": 0
}
stoploss = -0.294
def informative_pairs(self):
pairs = self.dp.current_whitelist()
informative_pairs = [(pair, self.informative_timeframe)
for pair in pairs]
return informative_pairs
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
displacement = 26
ichimoku = ftt.ichimoku(dataframe,
conversion_line_period=9,
base_line_periods=26,
laggin_span=52,
displacement=displacement
)
dataframe['chikou_span'] = ichimoku['chikou_span']
# cross indicators
dataframe['tenkan_sen'] = ichimoku['tenkan_sen']
dataframe['kijun_sen'] = ichimoku['kijun_sen']
# cloud, green a > b, red a < b
dataframe['senkou_a'] = ichimoku['senkou_span_a']
dataframe['senkou_b'] = ichimoku['senkou_span_b']
dataframe['leading_senkou_span_a'] = ichimoku['leading_senkou_span_a']
dataframe['leading_senkou_span_b'] = ichimoku['leading_senkou_span_b']
dataframe['cloud_green'] = ichimoku['cloud_green'] * 1
dataframe['cloud_red'] = ichimoku['cloud_red'] * -1
dataframe.loc[:, 'cloud_top'] = dataframe.loc[:,
['senkou_a', 'senkou_b']].max(axis=1)
dataframe.loc[:, 'cloud_bottom'] = dataframe.loc[:,
['senkou_a', 'senkou_b']].min(axis=1)
# DANGER ZONE START
# NOTE: Not actually the future, present data that is normally shifted forward for display as the cloud
dataframe['future_green'] = (
dataframe['leading_senkou_span_a'] > dataframe['leading_senkou_span_b']).astype('int') * 2
dataframe['future_red'] = (dataframe['leading_senkou_span_a']
< dataframe['leading_senkou_span_b']).astype('int') * 2
# The chikou_span is shifted into the past, so we need to be careful not to read the
# current value. But if we shift it forward again by displacement it should be safe to use.
# We're effectively "looking back" at where it normally appears on the chart.
dataframe['chikou_high'] = (
(dataframe['chikou_span'] > dataframe['cloud_top'])
).shift(displacement).fillna(0).astype('int')
dataframe['chikou_low'] = (
(dataframe['chikou_span'] < dataframe['cloud_bottom'])
).shift(displacement).fillna(0).astype('int')
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
conditions = []
conditions.append(
(
(dataframe['volume'] > 0)
)
)
if conditions:
dataframe.loc[
reduce(lambda x, y: x | y, conditions),
'buy'
]
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
conditions = []
conditions.append(
(
dataframe['volume'] > 0
)
)
if conditions:
dataframe.loc[
reduce(lambda x, y: x | y, conditions),
'sell'
]=1
return dataframe
def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount: float,
rate: float, time_in_force: str, sell_reason: str,
current_time: 'datetime', **kwargs) -> bool:
if sell_reason in ('roi',):
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
current_candle = dataframe.iloc[-1]
if current_candle is not None:
current_candle = current_candle.squeeze()
# don't sell during ichimoku uptrend
if current_candle['trending'] > 0:
return False
return True
plot_config = {
# Main plot indicators (Moving averages, ...)
'main_plot': {
'senkou_a': {
'color': 'green',
'fill_to': 'senkou_b',
'fill_label': 'Ichimoku Cloud',
'fill_color': 'rgba(0,0,0,0.2)',
},
# plot senkou_b, too. Not only the area to it.
'senkou_b': {
'color': 'red',
},
'tenkan_sen': {'color': 'blue'},
'kijun_sen': {'color': 'orange'},
# 'chikou_span': { 'color': 'lightgreen' },
'ssl_up': {'color': 'green'},
# 'ssl_down': { 'color': 'red' },
# 'ema50': { 'color': 'violet' },
# 'ema200': { 'color': 'magenta' },
'zema_buy': {'color': 'blue'},
'zema_sell': {'color': 'orange'},
},
'subplots': {
"Trend": {
'trending': {'color': 'green'},
'bear_trending': {'color': 'red'},
},
"Bull": {
'trend_pulse': {'color': 'blue'},
'trending': {'color': 'orange'},
'trend_over': {'color': 'red'},
},
"Bull Signals": {
'ichimoku_ok': {'color': 'green'},
'ssl_ok': {'color': 'red'},
},
"Bear": {
'bear_trend_pulse': {'color': 'blue'},
'bear_trending': {'color': 'orange'},
'bear_trend_over': {'color': 'red'},
},
"Bear Signals": {
'ichimoku_bear': {'color': 'green'},
'ssl_bear': {'color': 'red'},
},
"Misc": {
'ichimoku_valid': {'color': 'green'},
},
}
}