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modulation mise en fonction de max

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Jérôme Delacotte
2025-03-24 11:12:35 +01:00
parent 6b541837f1
commit 302efb588f
1 changed files with 100 additions and 137 deletions
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HeikinAshi.py
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@@ -129,6 +129,7 @@ class HeikinAshi(IStrategy):
pairs = {
pair: {
"last_max": 0,
"trade_info": {},
"max_touch": 0.0,
@@ -139,7 +140,8 @@ class HeikinAshi(IStrategy):
'expected_profit': 0,
"last_candle": {},
"last_trade": None,
'base_stake_amount': 0
'base_stake_amount': 0,
'stop_buy': False
}
for pair in ["BTC/USDT", "ETH/USDT", "DOGE/USDT", "DASH/USDT", "XRP/USDT", "SOL/USDT"]
}
@@ -164,7 +166,7 @@ class HeikinAshi(IStrategy):
dataframe, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
last_candle = dataframe.iloc[-1].squeeze()
# last_candle_decalage = dataframe.iloc[-1 - self.decalage.value].squeeze()
last_candle_3 = dataframe.iloc[-4].squeeze()
# last_candle_24 = dataframe.iloc[-25].squeeze()
# if (last_candle['sma5_diff_1d'] < -0.1):
@@ -176,67 +178,7 @@ class HeikinAshi(IStrategy):
dispo = round(self.wallets.get_available_stake_amount())
hours = (current_time - trade.date_last_filled_utc).total_seconds() / 3600.0
# if (current_profit > 0.008) \
# and (last_candle['up_pct'] >= 1)\
# and (last_candle['volume'] >= 250) \
# and (hours >= 1):
# additional_stake = self.config['stake_amount']
# self.log_trade(
# last_candle=last_candle,
# date=current_time,
# action="Gain +",
# dispo=dispo,
# pair=trade.pair,
# rate=current_rate,
# trade_type='Increase',
# profit=round(current_profit, 4), # round(current_profit * trade.stake_amount, 2),
# buys=trade.nr_of_successful_entries,
# stake=round(additional_stake, 2)
# )
# # self.pairs[trade.pair]['last_max'] = last_candle['haclose']
# self.pairs[trade.pair]['max_touch'] = last_candle['haclose']
# return additional_stake
# if (last_candle['percent'] > 0.001) and (current_profit > 0):
# # and (last_candle_decalage['min12'] == last_candle['min12']) \
# # and (last_candle_decalage['close'] < last_candle_decalage['mid288']):
# additional_stake = self.config['stake_amount'] / 10
# self.log_trade(
# last_candle=last_candle,
# date=current_time,
# action="Gain +",
# dispo=dispo,
# pair=trade.pair,
# rate=current_rate,
# trade_type='Increase',
# profit=round(current_profit, 4), # round(current_profit * trade.stake_amount, 2),
# buys=trade.nr_of_successful_entries,
# stake=round(additional_stake, 2)
# )
# return additional_stake
max_touch = self.pairs[trade.pair]['max_touch']
pct_max = - round(100 * (last_candle['close'] - max_touch) / max_touch, 1)
# if (last_candle['enter_long'] == 1) and (current_profit < - 0.0075 or hours >= 1) and (count_of_buys == 1):
# additional_stake = self.config['stake_amount'] / 2
# self.log_trade(
# last_candle=last_candle,
# date=current_time,
# action="Long",
# dispo=dispo,
# pair=trade.pair,
# rate=current_rate,
# trade_type='Increase',
# profit=round(current_profit, 4), # round(current_profit * trade.stake_amount, 2),
# buys=trade.nr_of_successful_entries + 1,
# stake=round(additional_stake, 2)
# )
# self.expectedProfit(trade.pair, last_candle, current_rate)
# self.pairs[trade.pair]['last_buy'] = current_rate
# self.pairs[trade.pair]['max_touch'] = last_candle['close']
# self.pairs[trade.pair]['last_candle'] = last_candle
#
# return additional_stake
limit_buy = 5
if (count_of_buys < limit_buy) \
@@ -252,7 +194,7 @@ class HeikinAshi(IStrategy):
dispo=dispo,
pair=trade.pair,
rate=current_rate,
trade_type='Decrease',
trade_type=last_candle['enter_tag'],
profit=round(current_profit, 4), # round(current_profit * trade.stake_amount, 2),
buys=trade.nr_of_successful_entries + 1,
stake=round(additional_stake, 2)
@@ -264,29 +206,11 @@ class HeikinAshi(IStrategy):
return additional_stake
# if (count_of_buys == limit_buy) & (current_profit < - 0.03 * count_of_buys)\
# and ((last_candle['enter_long'] == 1) or last_candle['percent48'] < - 0.03):
# additional_stake = - trade.stake_amount / 2 #self.config['stake_amount'] * (-current_profit / 0.10)
# self.log_trade(
# last_candle=last_candle,
# date=current_time,
# action="Loss -",
# dispo=dispo,
# pair=trade.pair,
# rate=current_rate,
# trade_type='Decrease',
# profit=round(current_profit, 4), # round(current_profit * trade.stake_amount, 2),
# buys=trade.nr_of_successful_entries,
# stake=round(additional_stake, 2)
# )
# # self.pairs[trade.pair]['last_max'] = last_candle['haclose']
# self.pairs[trade.pair]['max_touch'] = last_candle['haclose']
# return additional_stake
pct_limit = (-0.015 * limit_buy) + (- 0.03 * (count_of_buys - limit_buy))
if (count_of_buys >= limit_buy) & (current_profit < pct_limit) \
and ((last_candle['enter_long'] == 1) or last_candle['percent48'] < - 0.03):
additional_stake = self.calculate_stake(trade.pair, last_candle, 1) * (-current_profit / 0.10)
if (count_of_buys >= limit_buy) and (current_profit < pct_limit) \
and ((last_candle['enter_long'] == 1) or
(last_candle['percent48'] < - 0.03 and last_candle['min200'] == last_candle_3['min200'])):
additional_stake = self.calculate_stake(trade.pair, last_candle, 1) * (-current_profit / 0.1)
self.log_trade(
last_candle=last_candle,
date=current_time,
@@ -294,7 +218,7 @@ class HeikinAshi(IStrategy):
dispo=dispo,
pair=trade.pair,
rate=current_rate,
trade_type='Decrease',
trade_type=last_candle['enter_tag'],
profit=round(current_profit, 4), # round(current_profit * trade.stake_amount, 2),
buys=trade.nr_of_successful_entries + 1,
stake=round(additional_stake, 2)
@@ -306,6 +230,26 @@ class HeikinAshi(IStrategy):
return additional_stake
# if (current_profit > 0) and (count_of_buys >= limit_buy) and (hours > 24) and (last_candle['enter_long'] == 1):
# additional_stake = self.calculate_stake(trade.pair, last_candle, 1)
# self.log_trade(
# last_candle=last_candle,
# date=current_time,
# action="Gain +",
# dispo=dispo,
# pair=trade.pair,
# rate=current_rate,
# trade_type=last_candle['enter_tag'],
# profit=round(current_profit, 4), # round(current_profit * trade.stake_amount, 2),
# buys=trade.nr_of_successful_entries + 1,
# stake=round(additional_stake, 2)
# )
# self.expectedProfit(trade.pair, last_candle, current_rate)
# self.pairs[trade.pair]['last_buy'] = current_rate
# self.pairs[trade.pair]['max_touch'] = last_candle['close']
# self.pairs[trade.pair]['last_candle'] = last_candle
#
# return additional_stake
return None
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
@@ -316,30 +260,29 @@ class HeikinAshi(IStrategy):
# Obtenir les données actuelles pour cette paire
last_candle = dataframe.iloc[-1].squeeze()
stake_amount = self.config['stake_amount']
# if last_candle['close'] < last_candle['max5_1d'] * 0.98 :
# stake_amount = 2 * stake_amount
# else:
# if last_candle['close'] > last_candle['max5_1d'] * 1.02:
# stake_amount = 0.5 * stake_amount
# if last_candle['entry_tag'] == 'buy_hammer':
# stake_amount = stake_amount * 2
m = max(last_candle['max12_1d'], current_rate)
if last_candle['max12_1d'] > 0:
if (last_candle['close'] < m * 0.90):
stake_amount = stake_amount * 3
else:
if (last_candle['close'] < m * 0.95):
stake_amount = stake_amount * 2
return stake_amount
def calculate_stake(self, pair, last_candle, factor=1):
# if self.pairs[pair]['count_of_buys'] == 1 and factor == 1:
# if last_candle['close'] > last_candle['min5_1d'] + (last_candle['max5_1d'] - last_candle['min5_1d']) / 2:
# factor = 0.5
# amount = self.config['stake_amount'] * factor
# else:
# amount = self.config['stake_amount']
# self.pairs[pair]['base_stake_amount'] = amount
# else:
# amount = max(self.config['stake_amount'], self.pairs[pair]['base_stake_amount'])
stake_amount = self.config['stake_amount']
m = max(last_candle['max12_1d'], last_candle['close'])
amount = self.config['stake_amount']
return amount
if last_candle['max12_1d'] > 0:
if (last_candle['close'] < m * 0.90):
stake_amount = stake_amount * 3
else:
if (last_candle['close'] < m * 0.95):
stake_amount = stake_amount * 2
return stake_amount
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, time_in_force: str,
current_time: datetime, entry_tag: Optional[str], **kwargs) -> bool:
@@ -361,12 +304,28 @@ class HeikinAshi(IStrategy):
# return False
self.pairs[pair]['last_buy'] = rate
self.pairs[pair]['max_touch'] = last_candle['close']
self.pairs[pair]['last_max'] = last_candle['close']
self.pairs[pair]['last_candle'] = last_candle
self.pairs[pair]['count_of_buys'] = 1
self.pairs[pair]['current_profit'] = 0
stake_amount = self.calculate_stake(pair, last_candle, 1)
# if self.pairs[pair]['stop_buy']:
# if last_candle['sma5_diff_1d'] > 0:
# self.pairs[pair]['stop_buy'] = False
# else:
# self.log_trade(
# last_candle=last_candle,
# date=current_time,
# action="CANCEL BUY",
# pair=pair,
# rate=rate,
# dispo=dispo,
# profit=0,
# trade_type='stop_buy',
# buys=1,
# stake=0
# )
# return False
# self.columns_logged = False
print(
f"|{'-' * 18}+{'-' * 12}+{'-' * 12}+{'-' * 20}+{'-' * 14}+{'-' * 8}+{'-' * 10}+{'-' * 7}+{'-' * 13}+{'-' * 14}+{'-' * 14}+{'-' * 7}+{'-' * 12}|"
@@ -411,7 +370,6 @@ class HeikinAshi(IStrategy):
dispo=dispo,
profit=round(trade.calc_profit(rate, amount), 2)
)
self.pairs[pair]['last_max'] = 0
self.pairs[pair]['max_touch'] = 0
self.pairs[pair]['last_buy'] = 0
@@ -426,7 +384,6 @@ class HeikinAshi(IStrategy):
before_last_candle = dataframe.iloc[-2].squeeze()
max_touch_before = self.pairs[pair]['max_touch']
last_max_before = self.pairs[pair]['last_max']
self.pairs[pair]['last_max'] = max(last_candle['haclose'], self.pairs[pair]['last_max'])
last_lost = (last_candle['close'] - max_touch_before) / max_touch_before
@@ -444,14 +401,13 @@ class HeikinAshi(IStrategy):
# print(
# f"{current_time} days={days} expected={expected_profit:.3f} rate={current_rate} max_touch={max_touch_before:.1f} profit={current_profit:.3f} last_lost={last_lost:.3f} buys={count_of_buys} percent={last_candle['percent']:.4f}")
# if count_of_buys >= 5 and current_profit < 0 and (last_candle['percent12'] < -0.015):
# self.pairs[pair]['stop_buy'] = True
# return 'count_' + str(count_of_buys)
if (current_profit > expected_profit) \
& (last_candle['percent'] < 0.0) \
& (last_candle['percent5'] < 0.0) \
& (last_lost > - current_profit / 5):
# & (before_last_candle['hasma5'] < last_candle['hasma5']):
# & (last_lost < min(-0.003, - min(0.006, current_profit / 4))):
# & (last_candle['up_count'] > 0):
return 'last_lost_' + str(count_of_buys)
self.pairs[pair]['max_touch'] = max(last_candle['haclose'], self.pairs[pair]['max_touch'])
@@ -460,7 +416,7 @@ class HeikinAshi(IStrategy):
# & (last_candle['percent3'] < - min(0.01, current_profit / 4)):
# return 'profit_' + str(count_of_buys)
def detect_loose_hammer(self, df: DataFrame) -> DataFrame:
def detect_loose_hammer(self, df: DataFrame, fact=2.5) -> DataFrame:
"""
Détection large de marteaux : accepte des corps plus gros, ne vérifie pas le volume,
ne demande pas de divergence, juste un pattern visuel simple.
@@ -472,14 +428,14 @@ class HeikinAshi(IStrategy):
# Critères simplifiés :
df['loose_hammer'] = (
(lower_shadow > body * 2.5) # mèche basse > 1.5x corps
(lower_shadow > body * fact) # mèche basse > corps
& (upper_shadow < body) # petite mèche haute
& (df['low'] < df['bb_lowerband']) # bougie verte (optionnel, on peut prendre aussi les rouges)
& (df['low'] < df['bb_lowerband'])
).astype(int)
df['won_hammer'] = (
(upper_shadow > body * 2.5) # mèche basse > 1.5x corps
(upper_shadow > body * fact) # mèche basse > corps
& (lower_shadow < body) # petite mèche haute
& (df['high'] > df['bb_upperband']) # bougie verte (optionnel, on peut prendre aussi les rouges)
& (df['high'] > df['bb_upperband'])
).astype(int)
return df
@@ -488,7 +444,6 @@ class HeikinAshi(IStrategy):
last_buy = self.pairs[pair]['last_buy']
max_touch = self.pairs[pair]['max_touch']
last_max = self.pairs[pair]['last_max']
expected_profit = ((max_touch - last_buy) / max_touch)
self.pairs[pair]['expected_profit'] = max(0.004, expected_profit)
@@ -532,28 +487,19 @@ class HeikinAshi(IStrategy):
# action = self.color_line(action, action)
sma5_1d = ''
sma5_1h = ''
# if last_candle['sma5_pct_1d'] is not None:
# sma5_1d = round(last_candle['sma5_pct_1d'] * 100, 2)
# if last_candle['sma5_pct_1h'] is not None:
# sma5_1h = round(last_candle['sma5_pct_1h'] * 100, 2)
sma5 = str(sma5_1d) + ' ' + str(sma5_1h)
first_rate = self.pairs[pair]['last_max']
# if action != 'Sell':
# profit = round((last_candle['close'] - self.pairs[pair]['last_max']) / self.pairs[pair]['last_max'], 2)
sma5 = str(sma5_1d) + ' ' + str(sma5_1h)
last_lost = round((last_candle['haclose'] - self.pairs[pair]['max_touch']) / self.pairs[pair]['max_touch'], 3)
limit_sell = rsi_pct # round((last_candle['close'] - self.pairs[pair]['last_max']) / self.pairs[pair]['last_max'], 4)
max_touch = round(self.pairs[pair]['max_touch'],
1) # last_candle['max7_1d'] #round(100 * (last_candle['close'] - self.pairs[pair]['last_max']) / self.pairs[pair]['last_max'], 1)
pct_max = round(100 * self.pairs[pair]['current_profit'],
1) # round(100 * (last_candle['close'] - max_touch) / max_touch, 1)
max_touch = round(self.pairs[pair]['max_touch'], 1)
pct_max = round(100 * self.pairs[pair]['current_profit'], 1)
if trade_type is not None:
trade_type = trade_type + " " + str(round(100 * self.pairs[pair]['expected_profit'], 1))
print(
f"| {date:<16} | {action:<10} | {pair:<10} | {trade_type or '-':<18} | {rate or '-':>12} | {dispo or '-':>6} | {profit or '-':>8} | {pct_max or '-':>5} | {max_touch or '-':>11} | {last_lost or '-':>12} | {round(self.pairs[pair]['last_max'], 2) or '-':>12} | {self.pairs[pair]['count_of_buys'] or '-':>5} | {stake or '-':>10} |"
f"| {date:<16} | {action:<10} | {pair:<10} | {trade_type or '-':<18} | {rate or '-':>12} | {dispo or '-':>6} | {profit or '-':>8} | {pct_max or '-':>5} | {max_touch or '-':>11} | {last_lost or '-':>12} | {round(self.pairs[pair]['last_max'], 2) or '-':>12} | {buys or '-':>5} | {stake or '-':>10} |"
)
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -575,12 +521,17 @@ class HeikinAshi(IStrategy):
dataframe['min288'] = talib.MIN(dataframe['close'], timeperiod=288)
dataframe['max288'] = talib.MAX(dataframe['close'], timeperiod=288)
dataframe['mid288'] = dataframe['min288'] + (dataframe['max288'] - dataframe['min288']) / 2
dataframe['min200'] = talib.MIN(dataframe['close'], timeperiod=200)
dataframe['max200'] = talib.MAX(dataframe['close'], timeperiod=200)
dataframe['min_max200'] = (dataframe['max200'] - dataframe['min200']) / dataframe['min200']
dataframe["percent"] = (dataframe["close"] - dataframe["open"]) / dataframe["open"]
dataframe["percent3"] = dataframe['close'].pct_change(3)
dataframe["percent5"] = dataframe['close'].pct_change(5)
dataframe["percent12"] = dataframe['close'].pct_change(12)
dataframe["percent48"] = dataframe['close'].pct_change(48)
dataframe['average_line_288'] = talib.MIDPOINT(dataframe['close'], timeperiod=288)
# Bollinger Bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
@@ -606,6 +557,10 @@ class HeikinAshi(IStrategy):
# # ======================================================================================Decrease
# ################### INFORMATIVE 1d
informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe="1d")
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
informative['bb_lowerband'] = bollinger['lower']
informative['bb_middleband'] = bollinger['mid']
informative['bb_upperband'] = bollinger['upper']
# # Moving Averages
# informative['ema5'] = EMAIndicator(informative['close'], window=5).ema_indicator()
# informative['ema20'] = EMAIndicator(informative['close'], window=20).ema_indicator()
@@ -618,9 +573,9 @@ class HeikinAshi(IStrategy):
informative['max12'] = talib.MAX(informative['close'], timeperiod=12)
informative['min5'] = talib.MIN(informative['close'], timeperiod=5)
informative['min12'] = talib.MIN(informative['close'], timeperiod=12)
informative['sma5'] = talib.SMA(informative, timeperiod=25)
informative['sma5'] = talib.SMA(informative, timeperiod=5)
informative['sma5_diff'] = 100 * (informative['sma5'] - informative['sma5'].shift(1)) / informative['sma5']
# informative = self.detect_loose_hammer(informative)
informative = self.detect_loose_hammer(informative, 1.5)
dataframe = merge_informative_pair(dataframe, informative, self.timeframe, "1d", ffill=True)
@@ -673,12 +628,20 @@ class HeikinAshi(IStrategy):
)
& (dataframe['down_count'] == 0)
,
['enter_long', 'enter_tag']] = [1, 'buy_down']
['enter_long', 'enter_tag']] = [1, 'down']
dataframe.loc[(dataframe['loose_hammer'] == 1)
,
['enter_long', 'enter_tag']] = [1, 'buy_hammer']
['enter_long', 'enter_tag']] = [1, 'hammer']
# dataframe.loc[
# (
# (dataframe['low'] <= dataframe['min200'])
# # & (dataframe['min_max200'] > 0.015)
# # & (dataframe['percent5'] < 0)
# # & (dataframe['haopen'] < buy_level)
# # & (dataframe['open'] < dataframe['average_line_288'])
# & (dataframe['min200'].shift(3) == dataframe['min200'])
# ), ['enter_long', 'enter_tag']] = (1, 'min200')
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: