From d18dd5abff9cb04f26c7ec39bd745c7e46ccd4f3 Mon Sep 17 00:00:00 2001 From: Masoud Azizi Date: Thu, 19 Aug 2021 15:43:15 +0000 Subject: [PATCH] name changed and many other changes(Now Its the pure Dimond) name changed and many other changes(Now Its the pure Dimond) --- user_data/strategies/AfghanWoman.py | 133 ------------------------- user_data/strategies/Dimond.py | 147 ++++++++++++++++++++++++++++ 2 files changed, 147 insertions(+), 133 deletions(-) delete mode 100644 user_data/strategies/AfghanWoman.py create mode 100644 user_data/strategies/Dimond.py diff --git a/user_data/strategies/AfghanWoman.py b/user_data/strategies/AfghanWoman.py deleted file mode 100644 index 53369ef..0000000 --- a/user_data/strategies/AfghanWoman.py +++ /dev/null @@ -1,133 +0,0 @@ -# It is AfghanWoman Strategy. -# That takes her own rights like Afghanstan women -# Those who still proud and hopeful. -# Those who the most beautiful creatures in the depths of the darkest. -# Those who shine like diamonds buried in the heart of the desert ... -# Why not help when we can? -# If we believe there is no man left with them -# (Which is probably the product of the thought of painless corpses) -# Where has our humanity gone? -# Where has humanity gone? -# Why not help when we can? - -# Author: @Mablue (Masoud Azizi) -# github: https://github.com/mablue/ -# (First Hyperopt it.A hyperopt file is available) -# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLoss --spaces buy sell --strategy AfghanWoman -j 2 -# freqtrade backtesting --strategy AfghanWoman - -# --- Do not remove these libs --- -from freqtrade.strategy.hyper import IntParameter -from freqtrade.strategy.interface import IStrategy -from pandas import DataFrame -# -------------------------------- - -# Add your lib to import here -import talib.abstract as ta -from functools import reduce - -##### SETINGS ##### -# It hyperopt just one set of params for all buy and sell strategies if true. -DUALFIT = False -# how much Candles to check trand -TCC = 1 -### END SETINGS ### - - -class AfghanWoman(IStrategy): - # ###################### RESULT PLACE ###################### - # * 4/100: 80 trades. 28/0/52 Wins/Draws/Losses. Avg profit 2.64%. Median profit -0.19%. Total profit 3366.29721754 USDT ( 336.63Σ%). Avg duration 9:09:00 min. Objective: -8.35746 - - # Buy hyperspace params: - buy_params = { - "buy_count": 2, - "buy_gap": 15, - "buy_shift": 14, - } - - # Sell hyperspace params: - sell_params = { - "sell_count": 5, - "sell_gap": 13, - "sell_shift": 4, - } - # ROI table: - minimal_roi = { - "0": 1, - "13": 1, - "64": 1, - "178": 1 - } - # Stoploss: - stoploss = -0.256 - - # Buy hypers - timeframe = '5m' - # #################### END OF RESULT PLACE #################### - buy_count = IntParameter(2, 25, default=6, space='buy') - buy_gap = IntParameter(2, 25, default=13, space='buy') - buy_shift = IntParameter(0, 25, default=14, space='buy') - if not DUALFIT: - sell_count = IntParameter(2, 25, default=20, space='sell') - sell_gap = IntParameter(2, 25, default=3, space='sell') - sell_shift = IntParameter(0, 25, default=0, space='sell') - - def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - dataframe['PLUS_DM'] = ta.PLUS_DM(dataframe, timeperiod=14) - dataframe['MINUS_DM'] = ta.MINUS_DM(dataframe, timeperiod=14) - return dataframe - - def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - conditions = [] - conditions.append(dataframe['PLUS_DM'] > dataframe['MINUS_DM']) - count = gap = shift = None - - count = self.buy_count.value - gap = self.buy_gap.value - shift = self.buy_shift.value - - for i in range(1, count+1): - dataframe[f'buy-ma-{i}'] = ta.EMA(dataframe, - timeperiod=int(i * gap)) - for s in range(1, shift+1): - if i > 1: - conditions.append( - dataframe[f'buy-ma-{i}'].shift(s) > - dataframe[f'buy-ma-{i-1}'].shift(s) - ) - if conditions: - dataframe.loc[ - reduce(lambda x, y: x & y, conditions), - 'buy']=1 - - return dataframe - - def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - conditions = [] - conditions.append(dataframe['PLUS_DM'] <= dataframe['MINUS_DM']) - - count = gap = shift = None - - if DUALFIT: - count = self.buy_count.value - gap = self.buy_gap.value - shift = self.buy_shift.value - else: - count = self.sell_count.value - gap = self.sell_gap.value - shift = self.sell_shift.value - for i in range(1, count+1): - dataframe[f'buy-ma-{i}'] = ta.EMA(dataframe, - timeperiod=int(i * gap)) - for s in range(1, shift+1): - if i > 1: - conditions.append( - dataframe[f'buy-ma-{i}'].shift(s) < - dataframe[f'buy-ma-{i-1}'].shift(s) - ) - - if conditions: - dataframe.loc[ - reduce(lambda x, y: x & y, conditions), - 'sell']=1 - return dataframe diff --git a/user_data/strategies/Dimond.py b/user_data/strategies/Dimond.py new file mode 100644 index 0000000..554cc8e --- /dev/null +++ b/user_data/strategies/Dimond.py @@ -0,0 +1,147 @@ +# 𝐼𝓉 𝒾𝓈 𝒟𝒾𝓂𝑜𝓃𝒹 𝒮𝓉𝓇𝒶𝓉𝑒𝑔𝓎. +# 𝒯𝒽𝒶𝓉 𝓉𝒶𝓀𝑒𝓈 𝒽𝑒𝓇 𝑜𝓌𝓃 𝓇𝒾𝑔𝒽𝓉𝓈 𝓁𝒾𝓀𝑒 𝒜𝒻𝑔𝒽𝒶𝓃𝒾𝓈𝓉𝒶𝓃 𝓌𝑜𝓂𝑒𝓃 +# 𝒯𝒽𝑜𝓈𝑒 𝓌𝒽𝑜 𝓈𝓉𝒾𝓁𝓁 𝓅𝓇𝑜𝓊𝒹 𝒶𝓃𝒹 𝒽𝑜𝓅𝑒𝒻𝓊𝓁. +# 𝒯𝒽𝑜𝓈𝑒 𝓌𝒽𝑜 𝓉𝒽𝑒 𝓂𝑜𝓈𝓉 𝒷𝑒𝒶𝓊𝓉𝒾𝒻𝓊𝓁 𝒸𝓇𝑒𝒶𝓉𝓊𝓇𝑒𝓈 𝒾𝓃 𝓉𝒽𝑒 𝒹𝑒𝓅𝓉𝒽𝓈 𝑜𝒻 𝓉𝒽𝑒 𝒹𝒶𝓇𝓀𝑒𝓈𝓉. +# 𝒯𝒽𝑜𝓈𝑒 𝓌𝒽𝑜 𝓈𝒽𝒾𝓃𝑒 𝓁𝒾𝓀𝑒 𝒹𝒾𝒶𝓂𝑜𝓃𝒹𝓈 𝒷𝓊𝓇𝒾𝑒𝒹 𝒾𝓃 𝓉𝒽𝑒 𝒽𝑒𝒶𝓇𝓉 𝑜𝒻 𝓉𝒽𝑒 𝒹𝑒𝓈𝑒𝓇𝓉 ... +# 𝒲𝒽𝓎 𝓃𝑜𝓉 𝒽𝑒𝓁𝓅 𝓌𝒽𝑒𝓃 𝓌𝑒 𝒸𝒶𝓃? +# 𝐼𝒻 𝓌𝑒 𝒷𝑒𝓁𝒾𝑒𝓋𝑒 𝓉𝒽𝑒𝓇𝑒 𝒾𝓈 𝓃𝑜 𝓂𝒶𝓃 𝓁𝑒𝒻𝓉 𝓌𝒾𝓉𝒽 𝓉𝒽𝑒𝓂 +# (𝒲𝒽𝒾𝒸𝒽 𝒾𝓈 𝓅𝓇𝑜𝒷𝒶𝒷𝓁𝓎 𝓉𝒽𝑒 𝓅𝓇𝑜𝒹𝓊𝒸𝓉 𝑜𝒻 𝓉𝒽𝑒 𝓉𝒽𝑜𝓊𝑔𝒽𝓉 𝑜𝒻 𝓅𝒶𝒾𝓃𝓁𝑒𝓈𝓈 𝒸𝑜𝓇𝓅𝓈𝑒𝓈) +# 𝒲𝒽𝑒𝓇𝑒 𝒽𝒶𝓈 𝑜𝓊𝓇 𝒽𝓊𝓂𝒶𝓃𝒾𝓉𝓎 𝑔𝑜𝓃𝑒? +# 𝒲𝒽𝑒𝓇𝑒 𝒽𝒶𝓈 𝒽𝓊𝓂𝒶𝓃𝒾𝓉𝓎 𝑔𝑜𝓃𝑒? +# 𝒲𝒽𝓎 𝓃𝑜𝓉 𝒽𝑒𝓁𝓅 𝓌𝒽𝑒𝓃 𝓌𝑒 𝒸𝒶𝓃? +# IMPORTANT: This strategy +# designed for "ZERO" loss and "UNDER" +# 15 minuts avg duration.So if you have more +# loss and more avg, Its "NOT" normal result, and +# you will change config.json variables and hyperoption commands +# Thanks To @xmatthias if he was approve the last version of This strategy +# That just a lazy code. I never can reach to this strategy(Now its really a dimond.) +# * freqtrade hyperopt --hyperopt-loss ShortTradeDurHyperOptLoss --spaces all --strategy 𝒟𝒾𝓂𝑜𝓃𝒹 -e 700 -j 2 --timerange 20210810-20210813 +# * freqtrade backtesting --strategy 𝒟𝒾𝓂𝑜𝓃𝒹 +# Author: @Mablue (Masoud Azizi) +# github: https://github.com/mablue/ +# (First Hyperopt it.A hyperopt file is available) +# --- Do not remove these libs --- +from freqtrade.strategy.hyper import CategoricalParameter, DecimalParameter, IntParameter +from freqtrade.strategy.interface import IStrategy +from pandas import DataFrame +# -------------------------------- + +# Add your lib to import here +import talib.abstract as ta +from functools import reduce +import freqtrade.vendor.qtpylib.indicators as qtpylib + +##### SETINGS ##### +# It hyperopt just one set of params for all buy and sell strategies if true. +DUALFIT = False +COUNT = 10 +GAP = 3 +### END SETINGS ### + + +class Dimond(IStrategy): + # ###################### RESULT PLACE ###################### + # * 6/700: 1 trades. 1/0/0 Wins/Draws/Losses. Avg profit 17.68%. Median profit 17.68%. Total profit 58.94100000 USDT ( 5.89Σ%). Avg duration 0:00:00 min. Objective: 1.79949 + + # Buy hyperspace params: + buy_params = { + "buy_fast": 31, + "buy_push": 0.72, + "buy_shift": -7, + "buy_slow": 2, + } + + # Sell hyperspace params: + sell_params = { + "sell_fast": 17, + "sell_push": 1.493, + "sell_shift": -7, + "sell_slow": 28, + } + + # ROI table: + minimal_roi = { + "0": 0.177, + "31": 0.059, + "61": 0.021, + "170": 0 + } + + # Stoploss: + stoploss = -0.241 + + # Trailing stop: + trailing_stop = True + trailing_stop_positive = 0.13 + trailing_stop_positive_offset = 0.189 + trailing_only_offset_is_reached = True + # Buy hypers + timeframe = '5m' + # #################### END OF RESULT PLACE #################### + buy_push = DecimalParameter(0, 2, decimals=3, default=1, space='buy') + buy_shift = IntParameter(-10, 0, default=-6, space='buy') + buy_fast = IntParameter(2, 50, default=9, space='buy') + buy_slow = IntParameter(2, 50, default=18, space='buy') + if not DUALFIT: + sell_push = DecimalParameter( + 0, 2, decimals=3, default=1, space='sell') + sell_shift = IntParameter(-10, 0, default=-6, space='sell') + sell_fast = IntParameter(2, 50, default=9, space='sell') + sell_slow = IntParameter(2, 50, default=18, space='sell') + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + + return dataframe + + def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + dataframe['buy_ema_fast'] = ta.SMA( + dataframe, timeperiod=int(self.buy_fast.value)) + dataframe['buy_ema_slow'] = ta.SMA( + dataframe, timeperiod=int(self.buy_slow.value)) + + conditions = [] + + conditions.append( + qtpylib.crossed_above( + dataframe['buy_ema_fast'].shift(self.buy_shift.value), + dataframe['buy_ema_slow'].shift( + self.buy_shift.value)*self.buy_push.value + ) + ) + + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'buy']=1 + + return dataframe + + def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + push = self.buy_push.value + shift = self.buy_shift.value + ema_fast = dataframe['buy_ema_fast'] + ema_slow = dataframe['buy_ema_slow'] + + if not DUALFIT: + push = self.sell_push.value + shift = self.sell_shift.value + ema_fast = dataframe['sell_ema_fast'] = ta.SMA( + dataframe, timeperiod=int(self.buy_fast.value)) + ema_slow = dataframe['sell_ema_slow'] = ta.SMA( + dataframe, timeperiod=int(self.buy_slow.value)) + + conditions = [] + + conditions.append( + qtpylib.crossed_below( + ema_fast.shift(shift), + ema_slow.shift(shift)*push + ) + ) + + if conditions: + dataframe.loc[ + reduce(lambda x, y: x & y, conditions), + 'sell']=1 + return dataframe