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Update sample strategy with hyperoptable Parameters

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This commit is contained in:
Matthias 2021-04-03 16:32:16 +02:00
parent 093d6ce8af
commit 771fc05749
2 changed files with 15 additions and 5 deletions
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4
freqtrade/templates/base_strategy.py.j2
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@ -1,4 +1,5 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# --- Do not remove these libs --- # --- Do not remove these libs ---
import numpy as np # noqa import numpy as np # noqa
@ -6,6 +7,7 @@ import pandas as pd # noqa
from pandas import DataFrame from pandas import DataFrame
from freqtrade.strategy import IStrategy from freqtrade.strategy import IStrategy
from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter
# -------------------------------- # --------------------------------
# Add your lib to import here # Add your lib to import here
@ -16,7 +18,7 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
class {{ strategy }}(IStrategy): class {{ strategy }}(IStrategy):
""" """
This is a strategy template to get you started. This is a strategy template to get you started.
More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md More information in https://www.freqtrade.io/en/latest/strategy-customization/
You can: You can:
:return: a Dataframe with all mandatory indicators for the strategies :return: a Dataframe with all mandatory indicators for the strategies

16
freqtrade/templates/sample_strategy.py
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@ -1,11 +1,13 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file # isort: skip_file
# --- Do not remove these libs --- # --- Do not remove these libs ---
import numpy as np # noqa import numpy as np # noqa
import pandas as pd # noqa import pandas as pd # noqa
from pandas import DataFrame from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy from freqtrade.strategy import IStrategy
from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter
# -------------------------------- # --------------------------------
# Add your lib to import here # Add your lib to import here
@ -52,7 +54,11 @@ class SampleStrategy(IStrategy):
# trailing_stop_positive = 0.01 # trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured # trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy. # Hyperoptable parameters
buy_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
sell_rsi = IntParameter(low=50, high=100, defualt=70, space='buy', optimize=True, load=True)
# Optimal timeframe for the strategy.
timeframe = '5m' timeframe = '5m'
# Run "populate_indicators()" only for new candle. # Run "populate_indicators()" only for new candle.
@ -339,7 +345,8 @@ class SampleStrategy(IStrategy):
""" """
dataframe.loc[ dataframe.loc[
( (
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30 # Signal: RSI crosses above 30
(qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) &
(dataframe['tema'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle (dataframe['tema'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle
(dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising (dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising
(dataframe['volume'] > 0) # Make sure Volume is not 0 (dataframe['volume'] > 0) # Make sure Volume is not 0
@ -357,7 +364,8 @@ class SampleStrategy(IStrategy):
""" """
dataframe.loc[ dataframe.loc[
( (
(qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70 # Signal: RSI crosses above 70
(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) &
(dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle (dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle
(dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling (dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling
(dataframe['volume'] > 0) # Make sure Volume is not 0 (dataframe['volume'] > 0) # Make sure Volume is not 0