adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

adjusted to keep perfomance in percent consistent, while allowing to buy large swings

Browse Source
This commit is contained in:
Gert Wohlgemuth 2018-04-30 16:16:45 -07:00
parent ba476c201d
commit e0bdb6089e
1 changed files with 16 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

26
user_data/strategies/Quickie.py
View File

@ -23,6 +23,8 @@ class Quickie(IStrategy):
# This attribute will be overridden if the config file contains "minimal_roi" # This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = { minimal_roi = {
"100": 0.01, "100": 0.01,
"45": 0.02,
"30": 0.03,
"15": 0.06, "15": 0.06,
"10": 0.15, "10": 0.15,
} }
@ -35,13 +37,10 @@ class Quickie(IStrategy):
ticker_interval = 5 ticker_interval = 5
def populate_indicators(self, dataframe: DataFrame) -> DataFrame: def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
dataframe['sma_200'] = ta.SMA(dataframe,timeperiod=200) dataframe['sma_200'] = ta.SMA(dataframe, timeperiod=200)
dataframe['sma_50'] = ta.SMA(dataframe, timeperiod=50)
dataframe['adx'] = ta.ADX(dataframe) dataframe['adx'] = ta.ADX(dataframe)
# required for graphing # required for graphing
@ -55,10 +54,17 @@ class Quickie(IStrategy):
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame: def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
dataframe.loc[ dataframe.loc[
( (
(dataframe['adx'] > 30) & (
(dataframe['tema'] < dataframe['bb_middleband']) & (dataframe['adx'] > 30) &
(dataframe['tema'] > dataframe['tema'].shift(1)) & (dataframe['tema'] < dataframe['bb_middleband']) &
(dataframe['sma_200'] > dataframe['close']) (dataframe['tema'] > dataframe['tema'].shift(1)) &
(dataframe['sma_200'] > dataframe['close'])
)
|
(
(dataframe['sma_200'] > dataframe['close']) &
(dataframe['sma_50'] < dataframe['sma_200'])
)
), ),
'buy'] = 1 'buy'] = 1
return dataframe return dataframe