Merge pull request #134 from OtenMoten/master
Create HO-Strategy005.py and update Swing-High-To-Sky hyperopt and strategy.
This commit is contained in:
Matthias
@@ -0,0 +1,168 @@
|
||||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
|
||||
import talib.abstract as ta
|
||||
import numpy as np
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
from pandas import DataFrame
|
||||
from typing import Dict, Any, Callable, List
|
||||
from functools import reduce
|
||||
from skopt.space import Categorical, Dimension, Integer, Real
|
||||
from freqtrade.optimize.hyperopt_interface import IHyperOpt
|
||||
|
||||
__author__ = "Kevin Ossenbrueck"
|
||||
__github__ = "github.com/OtenMoten"
|
||||
__linkedin__ = "linkedin.com/in/kevin-ossenbrueck/?locale=en_US"
|
||||
__twitter__ = "twitter.com/ossenbrueck"
|
||||
__instagram__ = "instagram.com/kevin_ossenbrueck"
|
||||
__facebook__ = "facebook.com/kevin.ossenbrueck"
|
||||
__creator__ = ["github.com/xmatthias", "github.com/mishaker"]
|
||||
__credits__ = ["MontrealTradingGroup", "Udemy", "Mohsen Hassan", "Ilyass Tabiai"]
|
||||
__version__ = "3.0"
|
||||
__copyright__ = "GNU GPL"
|
||||
__status__ = "Live"
|
||||
|
||||
"""
|
||||
I was inspired by: https://github.com/freqtrade/freqtrade-strategies/blob/master/user_data/strategies/Strategy005.py
|
||||
Therefore, I wrote this hyperopt to make it more better. Thank you xmatthias and mishaker!
|
||||
"""
|
||||
|
||||
# Rolling volume range
|
||||
volumeAvgValueMin = 50
|
||||
volumeAvgValueMax = 300
|
||||
|
||||
# RSI range
|
||||
rsiValueMin = 1
|
||||
rsiValueMax = 100
|
||||
|
||||
# STOCH FAST range
|
||||
fastdValueMin = 1
|
||||
fastdValueMax = 100
|
||||
|
||||
# MINUS DI range
|
||||
minusdiValueMin = 1
|
||||
minusdiValueMax = 100
|
||||
|
||||
fishRsiNormaValueMin = 1
|
||||
fishRsiNormaValueMax = 100
|
||||
|
||||
|
||||
class HODobby(IHyperOpt):
|
||||
"""
|
||||
Hyperopt file for Strategy005
|
||||
"""
|
||||
|
||||
############### THIS STRATEGY IS DESIGNED FOR 5m TIMEFRAME ###############
|
||||
|
||||
@staticmethod
|
||||
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
# MACD
|
||||
# tadoc.org/indicator/MACD.htm
|
||||
macd = ta.MACD(dataframe)
|
||||
dataframe['macd'] = macd['macd']
|
||||
|
||||
# MINUS DI
|
||||
# tadoc.org/indicator/MINUS_DI.htm
|
||||
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
|
||||
|
||||
# RSI
|
||||
# tadoc.org/indicator/RSI.htm
|
||||
# tradingview.com/scripts/fishertransform/
|
||||
# goo.gl/2JGGoy
|
||||
dataframe['rsi'] = ta.RSI(dataframe)
|
||||
rsi = 0.1 * (dataframe['rsi'] - 50)
|
||||
dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) # Inverse Fisher transform on RSI, values [-1.0, 1.0]
|
||||
dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) # Inverse Fisher transform on RSI normalized, value [0.0, 100.0]
|
||||
|
||||
# STOCH FAST
|
||||
# tadoc.org/indicator/STOCHF.htm
|
||||
stoch_fast = ta.STOCHF(dataframe)
|
||||
dataframe['fastd'] = stoch_fast['fastd']
|
||||
dataframe['fastk'] = stoch_fast['fastk']
|
||||
|
||||
# SAR
|
||||
dataframe['sar'] = ta.SAR(dataframe)
|
||||
|
||||
# SMA
|
||||
dataframe['sma'] = ta.SMA(dataframe, timeperiod=50)
|
||||
|
||||
return dataframe
|
||||
|
||||
@staticmethod
|
||||
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
|
||||
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
conditions = []
|
||||
|
||||
# TRIGGER and GUARD
|
||||
if 'buy-trigger' in params:
|
||||
|
||||
conditions.append(dataframe['close'] > 0.00000200)
|
||||
conditions.append(dataframe['volume'] > dataframe['volume'].rolling(params['volumeAVG-buy-value']).mean())
|
||||
conditions.append(dataframe['close'] < dataframe['sma'])
|
||||
conditions.append(dataframe['rsi'] > params['rsi-buy-value'])
|
||||
conditions.append(dataframe['fastd'] > dataframe['fastk'])
|
||||
conditions.append(dataframe['fastd'] > params['fastd-buy-value'])
|
||||
conditions.append(dataframe['fisher_rsi_norma'] < params['fishRsiNorma-buy-value'])
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[reduce(lambda x, y: x & y, conditions), 'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_buy_trend
|
||||
|
||||
@staticmethod
|
||||
def indicator_space() -> List[Dimension]:
|
||||
|
||||
buyTriggerList = ["True"]
|
||||
|
||||
return [
|
||||
Integer(volumeAvgValueMin, volumeAvgValueMax, name='volumeAVG-buy-value'),
|
||||
Integer(rsiValueMin, rsiValueMax, name='rsi-buy-value'),
|
||||
Integer(fastdValueMin, fastdValueMax, name='fastd-buy-value'),
|
||||
Integer(fishRsiNormaValueMin, fishRsiNormaValueMax, name='fishRsiNorma-buy-value'),
|
||||
Categorical(buyTriggerList, name='buy-trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
|
||||
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
# TRIGGERS and GUARDS
|
||||
# Solving a mistery: Which sell trigger is better?
|
||||
# The winner of both will be displayed in the output of the hyperopt.
|
||||
|
||||
conditions = []
|
||||
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'rsi-macd-minusdi':
|
||||
conditions.append(qtpylib.crossed_above(dataframe['rsi'], params['rsi-sell-value']))
|
||||
conditions.append(dataframe['macd'] < 0)
|
||||
conditions.append(dataframe['minus_di'] > params['minusdi-sell-value'])
|
||||
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sar-fisherRsi':
|
||||
conditions.append(dataframe['sar'] > dataframe['close'])
|
||||
conditions.append(dataframe['fisher_rsi'] > params['fishRsiNorma-sell-value'])
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[reduce(lambda x, y: x & y, conditions), 'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_sell_trend
|
||||
|
||||
@staticmethod
|
||||
def sell_indicator_space() -> List[Dimension]:
|
||||
|
||||
sellTriggerList = ["rsi-macd-minusdi", "sar-fisherRsi"]
|
||||
|
||||
return [
|
||||
Integer(rsiValueMin, rsiValueMax, name='rsi-sell-value'),
|
||||
Integer(minusdiValueMin, minusdiValueMax, name='minusdi-sell-value'),
|
||||
Integer(fishRsiNormaValueMin, fishRsiNormaValueMax, name='fishRsiNorma-sell-value'),
|
||||
Categorical(sellTriggerList, name='sell-trigger')
|
||||
]
|
||||
@@ -20,26 +20,32 @@ __email__ = "kevin.ossenbrueck@pm.de"
|
||||
__status__ = "Live"
|
||||
|
||||
cciTimeMin = 10
|
||||
cciTimeMax = 100
|
||||
cciValueMin = -400
|
||||
cciValueMax = 400
|
||||
cciTimeMax = 80
|
||||
cciValueMin = -200
|
||||
cciValueMax = 200
|
||||
cciTimeRange = range(cciTimeMin, cciTimeMax)
|
||||
|
||||
class_name = 'HOSwingHighToSky'
|
||||
rsiTimeMin = 10
|
||||
rsiTimeMax = 80
|
||||
rsiValueMin = 10
|
||||
rsiValueMax = 90
|
||||
rsiTimeRange = range(rsiTimeMin, rsiTimeMax)
|
||||
|
||||
class HOSwingHighToSky(IHyperOpt):
|
||||
|
||||
@staticmethod
|
||||
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
macd = ta.MACD(dataframe)
|
||||
dataframe['macd'] = macd['macd']
|
||||
dataframe['macdsignal'] = macd['macdsignal']
|
||||
|
||||
for cciTime in cciTimeRange:
|
||||
|
||||
cciName = "cci-" + str(cciTime)
|
||||
dataframe[cciName] = ta.CCI(dataframe, timeperiod = cciTime)
|
||||
|
||||
for rsiTime in rsiTimeRange:
|
||||
|
||||
rsiName = "rsi-" + str(rsiTime)
|
||||
dataframe[rsiName] = ta.RSI(dataframe, timeperiod = rsiTime)
|
||||
|
||||
return dataframe
|
||||
|
||||
@staticmethod
|
||||
@@ -50,15 +56,24 @@ class HOSwingHighToSky(IHyperOpt):
|
||||
conditions = []
|
||||
|
||||
# TRIGGERS & GUARDS
|
||||
if 'trigger' in params:
|
||||
if 'cci-buy-trigger' in params:
|
||||
|
||||
for cciTime in cciTimeRange:
|
||||
|
||||
cciName = "cci-" + str(cciTime)
|
||||
|
||||
if params['trigger'] == cciName:
|
||||
conditions.append(dataframe[cciName] < params["buy-cci-value"])
|
||||
conditions.append(dataframe['macd'] > dataframe['macdsignal'])
|
||||
if params['cci-buy-trigger'] == cciName:
|
||||
conditions.append(dataframe[cciName] < params["cci-buy-value"])
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if 'rsi-buy-trigger' in params:
|
||||
|
||||
for rsiTime in rsiTimeRange:
|
||||
|
||||
rsiName = "rsi-" + str(rsiTime)
|
||||
|
||||
if params['rsi-buy-trigger'] == rsiName:
|
||||
conditions.append(dataframe[rsiName] < params["rsi-buy-value"])
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
@@ -71,16 +86,24 @@ class HOSwingHighToSky(IHyperOpt):
|
||||
@staticmethod
|
||||
def indicator_space() -> List[Dimension]:
|
||||
|
||||
buyTriggerList = []
|
||||
cciBuyTriggerList = []
|
||||
rsiBuyTriggerList = []
|
||||
|
||||
for cciTime in cciTimeRange:
|
||||
|
||||
cciName = "cci-" + str(cciTime)
|
||||
buyTriggerList.append(cciName)
|
||||
cciBuyTriggerList.append(cciName)
|
||||
|
||||
for rsiTime in rsiTimeRange:
|
||||
|
||||
rsiName = "rsi-" + str(rsiTime)
|
||||
rsiBuyTriggerList.append(rsiName)
|
||||
|
||||
return [
|
||||
Integer(cciValueMin, cciValueMax, name='buy-cci-value'),
|
||||
Categorical(buyTriggerList, name='trigger')
|
||||
Integer(cciValueMin, cciValueMax, name='cci-buy-value'),
|
||||
Integer(rsiValueMin, rsiValueMax, name='rsi-buy-value'),
|
||||
Categorical(cciBuyTriggerList, name='cci-buy-trigger'),
|
||||
Categorical(rsiBuyTriggerList, name='rsi-buy-trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
@@ -91,15 +114,23 @@ class HOSwingHighToSky(IHyperOpt):
|
||||
conditions = []
|
||||
|
||||
# TRIGGERS & GUARDS
|
||||
if 'sell-trigger' in params:
|
||||
if 'cci-sell-trigger' in params:
|
||||
|
||||
for cciTime in cciTimeRange:
|
||||
|
||||
cciName = "cci-" + str(cciTime)
|
||||
|
||||
if params['sell-trigger'] == cciName:
|
||||
conditions.append(dataframe[cciName] > params["sell-cci-value"])
|
||||
conditions.append(dataframe['macd'] < dataframe['macdsignal'])
|
||||
if params['cci-sell-trigger'] == cciName:
|
||||
conditions.append(dataframe[cciName] > params["cci-sell-value"])
|
||||
|
||||
if 'rsi-sell-trigger' in params:
|
||||
|
||||
for rsiTime in rsiTimeRange:
|
||||
|
||||
rsiName = "rsi-" + str(rsiTime)
|
||||
|
||||
if params['rsi-sell-trigger'] == rsiName:
|
||||
conditions.append(dataframe[rsiName] > params["rsi-sell-value"])
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[reduce(lambda x, y: x & y, conditions), 'sell'] = 1
|
||||
@@ -111,14 +142,22 @@ class HOSwingHighToSky(IHyperOpt):
|
||||
@staticmethod
|
||||
def sell_indicator_space() -> List[Dimension]:
|
||||
|
||||
sellTriggerList = []
|
||||
cciSellTriggerList = []
|
||||
rsiSellTriggerList = []
|
||||
|
||||
for cciTime in cciTimeRange:
|
||||
|
||||
cciName = "cci-" + str(cciTime)
|
||||
sellTriggerList.append(cciName)
|
||||
cciSellTriggerList.append(cciName)
|
||||
|
||||
for rsiTime in rsiTimeRange:
|
||||
|
||||
rsiName = "rsi-" + str(rsiTime)
|
||||
rsiSellTriggerList.append(rsiName)
|
||||
|
||||
return [
|
||||
Integer(cciValueMin, cciValueMax, name='sell-cci-value'),
|
||||
Categorical(sellTriggerList, name='sell-trigger')
|
||||
]
|
||||
Integer(cciValueMin, cciValueMax, name='cci-sell-value'),
|
||||
Integer(rsiValueMin, rsiValueMax, name='rsi-sell-value'),
|
||||
Categorical(cciSellTriggerList, name='cci-sell-trigger'),
|
||||
Categorical(rsiSellTriggerList, name='rsi-sell-trigger')
|
||||
]
|
||||
|
||||
@@ -1,13 +1,11 @@
|
||||
# --- 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
|
||||
import numpy # noqa
|
||||
import numpy
|
||||
|
||||
__author__ = "Kevin Ossenbrück"
|
||||
__copyright__ = "Free For Use"
|
||||
@@ -18,60 +16,56 @@ __maintainer__ = "Kevin Ossenbrück"
|
||||
__email__ = "kevin.ossenbrueck@pm.de"
|
||||
__status__ = "Live"
|
||||
|
||||
class_name = 'SwingHighToSky'
|
||||
# CCI timerperiods and values
|
||||
cciBuyTP = 72
|
||||
cciBuyVal = -175
|
||||
cciSellTP = 66
|
||||
cciSellVal = -106
|
||||
|
||||
# RSI timeperiods and values
|
||||
rsiBuyTP = 36
|
||||
rsiBuyVal = 90
|
||||
rsiSellTP = 45
|
||||
rsiSellVal = 88
|
||||
|
||||
class SwingHighToSky(IStrategy):
|
||||
|
||||
# Disable ROI
|
||||
# Could be replaced with new ROI from hyperopt.
|
||||
minimal_roi = {
|
||||
"0": 100
|
||||
}
|
||||
|
||||
stoploss = -0.30
|
||||
|
||||
### Do extra hyperopt for trailing seperat. Use "--spaces default" and then "--spaces trailing".
|
||||
### See here for more information: https://www.freqtrade.io/en/latest/hyperopt
|
||||
trailing_stop = True
|
||||
trailing_stop_positive = 0.08
|
||||
trailing_stop_positive_offset = 0.10
|
||||
trailing_only_offset_is_reached = True
|
||||
|
||||
ticker_interval = '30m'
|
||||
|
||||
ticker_interval = '15m'
|
||||
|
||||
stoploss = -0.34338
|
||||
|
||||
minimal_roi = {"0": 0.27058, "33": 0.0853, "64": 0.04093, "244": 0}
|
||||
|
||||
def informative_pairs(self):
|
||||
return []
|
||||
|
||||
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
macd = ta.MACD(dataframe)
|
||||
dataframe['macd'] = macd['macd']
|
||||
dataframe['macdsignal'] = macd['macdsignal']
|
||||
|
||||
### Add timeperiod from hyperopt (replace xx with value):
|
||||
### "xx" must be replaced even before the first hyperopt is run,
|
||||
### else "xx" would be a syntax error because it must be a Integer value.
|
||||
dataframe['cci-buy'] = ta.CCI(dataframe, timeperiod=xx)
|
||||
dataframe['cci-sell'] = ta.CCI(dataframe, timeperiod=xx)
|
||||
|
||||
dataframe['cci-'+str(cciBuyTP)] = ta.CCI(dataframe, timeperiod=cciBuyTP)
|
||||
dataframe['cci-'+str(cciSellTP)] = ta.CCI(dataframe, timeperiod=cciSellTP)
|
||||
|
||||
dataframe['rsi-'+str(rsiBuyTP)] = ta.RSI(dataframe, timeperiod=rsiBuyTP)
|
||||
dataframe['rsi-'+str(rsiSellTP)] = ta.RSI(dataframe, timeperiod=rsiSellTP)
|
||||
|
||||
return dataframe
|
||||
|
||||
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe['macd'] > dataframe['macdsignal']) &
|
||||
(dataframe['cci-buy'] <= -100.0) # Replace with value from hyperopt.
|
||||
(dataframe['cci-'+str(cciBuyTP)] < cciBuyVal) &
|
||||
(dataframe['rsi-'+str(rsiBuyTP)] < rsiBuyVal)
|
||||
),
|
||||
'buy'] = 1
|
||||
|
||||
|
||||
return dataframe
|
||||
|
||||
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe['macd'] < dataframe['macdsignal']) &
|
||||
(dataframe['cci-sell'] >= 200.0) # Replace with value from hyperopt.
|
||||
(dataframe['cci-'+str(cciSellTP)] > cciSellVal) &
|
||||
(dataframe['rsi-'+str(rsiSellTP)] > rsiSellVal)
|
||||
),
|
||||
'sell'] = 1
|
||||
|
||||
|
||||
Reference in New Issue
Block a user