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NostalgiaForInfinityNextGen.py
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2511 lines (2244 loc) · 147 KB
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import copy
import logging
import pathlib
import rapidjson
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
import talib.abstract as ta
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy import merge_informative_pair, timeframe_to_minutes
from freqtrade.exchange import timeframe_to_prev_date
from pandas import DataFrame, Series, concat
from functools import reduce
import math
from typing import Dict
from freqtrade.persistence import Trade
from datetime import datetime, timedelta
from technical.util import resample_to_interval, resampled_merge
from technical.indicators import zema, VIDYA, ichimoku
import time
log = logging.getLogger(__name__)
#log.setLevel(logging.DEBUG)
try:
import pandas_ta as pta
except ImportError:
log.error(
"IMPORTANT - please install the pandas_ta python module which is needed for this strategy. "
"If you're running Docker, add RUN pip install pandas_ta to your Dockerfile, otherwise run: "
"pip install pandas_ta"
)
else:
log.info("pandas_ta successfully imported")
###########################################################################################################
## NostalgiaForInfinityV9 by iterativ ##
## https://github.com/iterativv/NostalgiaForInfinity ##
## ##
## Strategy for Freqtrade https://github.com/freqtrade/freqtrade ##
## ##
###########################################################################################################
## GENERAL RECOMMENDATIONS ##
## ##
## For optimal performance, suggested to use between 4 and 6 open trades, with unlimited stake. ##
## A pairlist with 40 to 80 pairs. Volume pairlist works well. ##
## Prefer stable coin (USDT, BUSDT etc) pairs, instead of BTC or ETH pairs. ##
## Highly recommended to blacklist leveraged tokens (*BULL, *BEAR, *UP, *DOWN etc). ##
## Ensure that you don't override any variables in you config.json. Especially ##
## the timeframe (must be 15m). ##
## use_sell_signal must set to true (or not set at all). ##
## sell_profit_only must set to false (or not set at all). ##
## ignore_roi_if_buy_signal must set to true (or not set at all). ##
## ##
###########################################################################################################
## HOLD SUPPORT ##
## ##
## -------- SPECIFIC TRADES ---------------------------------------------------------------------------- ##
## In case you want to have SOME of the trades to only be sold when on profit, add a file named ##
## "nfi-hold-trades.json" in the user_data directory ##
## ##
## The contents should be similar to: ##
## ##
## {"trade_ids": [1, 3, 7], "profit_ratio": 0.005} ##
## ##
## Or, for individual profit ratios(Notice the trade ID's as strings: ##
## ##
## {"trade_ids": {"1": 0.001, "3": -0.005, "7": 0.05}} ##
## ##
## NOTE: ##
## * `trade_ids` is a list of integers, the trade ID's, which you can get from the logs or from the ##
## output of the telegram status command. ##
## * Regardless of the defined profit ratio(s), the strategy MUST still produce a SELL signal for the ##
## HOLD support logic to run ##
## * This feature can be completely disabled with the holdSupportEnabled class attribute ##
## ##
## -------- SPECIFIC PAIRS ----------------------------------------------------------------------------- ##
## In case you want to have some pairs to always be on held until a specific profit, using the same ##
## "hold-trades.json" file add something like: ##
## ##
## {"trade_pairs": {"BTC/USDT": 0.001, "ETH/USDT": -0.005}} ##
## ##
## -------- SPECIFIC TRADES AND PAIRS ------------------------------------------------------------------ ##
## It is also valid to include specific trades and pairs on the holds file, for example: ##
## ##
## {"trade_ids": {"1": 0.001}, "trade_pairs": {"BTC/USDT": 0.001}} ##
###########################################################################################################
## DONATIONS ##
## ##
## Absolutely not required. However, will be accepted as a token of appreciation. ##
## ##
## BTC: bc1qvflsvddkmxh7eqhc4jyu5z5k6xcw3ay8jl49sk ##
## ETH (ERC20): 0x83D3cFb8001BDC5d2211cBeBB8cB3461E5f7Ec91 ##
## BEP20/BSC (ETH, BNB, ...): 0x86A0B21a20b39d16424B7c8003E4A7e12d78ABEe ##
## ##
## REFERRAL LINKS ##
## ##
## Binance: https://accounts.binance.com/en/register?ref=37365811 ##
## Kucoin: https://www.kucoin.com/ucenter/signup?rcode=rJTLZ9K ##
## Huobi: https://www.huobi.com/en-us/topic/double-reward/?invite_code=ubpt2223 ##
###########################################################################################################
class NostalgiaForInfinityNextGen(IStrategy):
INTERFACE_VERSION = 2
# ROI table:
minimal_roi = {
"0": 100.0,
}
stoploss = -0.50
# Trailing stoploss (not used)
trailing_stop = False
trailing_only_offset_is_reached = True
trailing_stop_positive = 0.01
trailing_stop_positive_offset = 0.03
use_custom_stoploss = False
# Optimal timeframe for the strategy.
timeframe = '15m'
res_timeframe = 'none'
info_timeframe_1h = '1h'
info_timeframe_1d = '1d'
# BTC informative
has_BTC_base_tf = False
has_BTC_info_tf = True
has_BTC_daily_tf = False
# Backtest Age Filter emulation
has_bt_agefilter = False
bt_min_age_days = 3
# Exchange Downtime protection
has_downtime_protection = False
# Do you want to use the hold feature? (with hold-trades.json)
holdSupportEnabled = True
# Coin Metrics
coin_metrics = {}
coin_metrics['top_traded_enabled'] = False
coin_metrics['top_traded_updated'] = False
coin_metrics['top_traded_len'] = 10
coin_metrics['tt_dataframe'] = DataFrame()
coin_metrics['top_grossing_enabled'] = False
coin_metrics['top_grossing_updated'] = False
coin_metrics['top_grossing_len'] = 20
coin_metrics['tg_dataframe'] = DataFrame()
coin_metrics['current_whitelist'] = []
# Run "populate_indicators()" only for new candle.
process_only_new_candles = True
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = True
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 480
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'trailing_stop_loss': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False,
'stoploss_on_exchange_interval': 60,
'stoploss_on_exchange_limit_ratio': 0.99
}
#############################################################
buy_params = {
#############
# Enable/Disable conditions
"buy_condition_1_enable": True,
"buy_condition_2_enable": True,
"buy_condition_3_enable": True,
"buy_condition_4_enable": True,
"buy_condition_5_enable": True,
"buy_condition_6_enable": True,
"buy_condition_7_enable": True,
"buy_condition_8_enable": True,
#############
}
sell_params = {
#############
# Enable/Disable conditions
"sell_condition_1_enable": True,
#############
}
#############################################################
buy_protection_params = {
1: {
"ema_fast" : False,
"ema_fast_len" : "26",
"ema_slow" : False,
"ema_slow_len" : "12",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "28",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips_threshold_0" : None,
"safe_dips_threshold_2" : None,
"safe_dips_threshold_12" : None,
"safe_dips_threshold_144" : None,
"safe_pump_6h_threshold" : None,
"safe_pump_12h_threshold" : 0.2,
"safe_pump_24h_threshold" : 0.54,
"safe_pump_36h_threshold" : None,
"safe_pump_48h_threshold" : None,
"btc_1h_not_downtrend" : False,
"close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 1.0,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.0
},
2: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "12",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips_threshold_0" : 0.06,
"safe_dips_threshold_2" : None,
"safe_dips_threshold_12" : None,
"safe_dips_threshold_144" : None,
"safe_pump_6h_threshold" : None,
"safe_pump_12h_threshold" : 0.4,
"safe_pump_24h_threshold" : 0.6,
"safe_pump_36h_threshold" : 0.7,
"safe_pump_48h_threshold" : 0.8,
"btc_1h_not_downtrend" : True,
"close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 1.0,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.0
},
3: {
"ema_fast" : True,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "12",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "50",
"safe_dips_threshold_0" : 0.04,
"safe_dips_threshold_2" : 0.08,
"safe_dips_threshold_12" : 0.18,
"safe_dips_threshold_144" : 0.28,
"safe_pump_6h_threshold" : 0.2,
"safe_pump_12h_threshold" : None,
"safe_pump_24h_threshold" : None,
"safe_pump_36h_threshold" : None,
"safe_pump_48h_threshold" : None,
"btc_1h_not_downtrend" : False,
"close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 1.0,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.0
},
4: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "50",
"safe_dips_threshold_0" : 0.045,
"safe_dips_threshold_2" : 0.12,
"safe_dips_threshold_12" : 0.34,
"safe_dips_threshold_144" : 0.48,
"safe_pump_6h_threshold" : 0.19,
"safe_pump_12h_threshold" : None,
"safe_pump_24h_threshold" : None,
"safe_pump_36h_threshold" : None,
"safe_pump_48h_threshold" : None,
"btc_1h_not_downtrend" : False,
"close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 0.95,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.0
},
5: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "24",
"safe_dips_threshold_0" : 0.08,
"safe_dips_threshold_2" : 0.14,
"safe_dips_threshold_12" : 0.28,
"safe_dips_threshold_144" : 0.44,
"safe_pump_6h_threshold" : None,
"safe_pump_12h_threshold" : None,
"safe_pump_24h_threshold" : None,
"safe_pump_36h_threshold" : None,
"safe_pump_48h_threshold" : 1.5,
"btc_1h_not_downtrend" : False,
"close_over_pivot_type" : "sup3", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 1.0,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.3
},
6: {
"ema_fast" : False,
"ema_fast_len" : "12",
"ema_slow" : True,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "24",
"safe_dips_threshold_0" : 0.08,
"safe_dips_threshold_2" : 0.16,
"safe_dips_threshold_12" : 0.4,
"safe_dips_threshold_144" : 0.8,
"safe_pump_6h_threshold" : None,
"safe_pump_12h_threshold" : None,
"safe_pump_24h_threshold" : None,
"safe_pump_36h_threshold" : None,
"safe_pump_48h_threshold" : 1.3,
"btc_1h_not_downtrend" : False,
"close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 1.0,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.15
},
7: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : False,
"ema_slow_len" : "50",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "50",
"sma200_1h_rising" : False,
"sma200_1h_rising_val" : "24",
"safe_dips_threshold_0" : 0.05,
"safe_dips_threshold_2" : 0.1,
"safe_dips_threshold_12" : 0.2,
"safe_dips_threshold_144" : 0.6,
"safe_pump_6h_threshold" : None,
"safe_pump_12h_threshold" : None,
"safe_pump_24h_threshold" : None,
"safe_pump_36h_threshold" : None,
"safe_pump_48h_threshold" : None,
"btc_1h_not_downtrend" : True,
"close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 1.0,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.1
},
8: {
"ema_fast" : False,
"ema_fast_len" : "50",
"ema_slow" : True,
"ema_slow_len" : "12",
"close_above_ema_fast" : False,
"close_above_ema_fast_len" : "200",
"close_above_ema_slow" : False,
"close_above_ema_slow_len" : "200",
"sma200_rising" : False,
"sma200_rising_val" : "24",
"sma200_1h_rising" : True,
"sma200_1h_rising_val" : "50",
"safe_dips_threshold_0" : 0.04,
"safe_dips_threshold_2" : 0.18,
"safe_dips_threshold_12" : 0.48,
"safe_dips_threshold_144" : 0.9,
"safe_pump_6h_threshold" : None,
"safe_pump_12h_threshold" : None,
"safe_pump_24h_threshold" : None,
"safe_pump_36h_threshold" : None,
"safe_pump_48h_threshold" : 0.9,
"btc_1h_not_downtrend" : False,
"close_over_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_over_pivot_offset" : 1.0,
"close_under_pivot_type" : "none", # pivot, sup1, sup2, sup3, res1, res2, res3
"close_under_pivot_offset" : 1.15
}
}
# 5 hours - level 10
buy_dump_protection_10_5 = 0.4
# 5 hours - level 20
buy_dump_protection_20_5 = 0.44
# 5 hours - level 30
buy_dump_protection_30_5 = 0.50
# 5 hours - level 40
buy_dump_protection_40_5 = 0.58
# 5 hours - level 50
buy_dump_protection_50_5 = 0.66
# 5 hours - level 60
buy_dump_protection_60_5 = 0.74
# Sell
sell_condition_1_enable = True
# 48h for pump sell checks
sell_pump_threshold_48_1 = 0.9
sell_pump_threshold_48_2 = 0.7
sell_pump_threshold_48_3 = 0.5
# 36h for pump sell checks
sell_pump_threshold_36_1 = 0.72
sell_pump_threshold_36_2 = 4.0
sell_pump_threshold_36_3 = 1.0
# 24h for pump sell checks
sell_pump_threshold_24_1 = 0.68
sell_pump_threshold_24_2 = 0.62
sell_pump_threshold_24_3 = 0.88
sell_rsi_bb_1 = 74.0
sell_rsi_bb_2 = 75.0
sell_rsi_main_3 = 78.0
sell_dual_rsi_rsi_4 = 68.4
sell_dual_rsi_rsi_1h_4 = 74.6
sell_ema_relative_5 = 0.024
sell_rsi_diff_5 = 4.4
sell_rsi_under_6 = 74.0
sell_rsi_1h_7 = 76.7
sell_bb_relative_8 = 1.1
#############################################################
#############################################################
# CACHES
hold_trades_cache = None
target_profit_cache = None
#############################################################
def __init__(self, config: dict) -> None:
super().__init__(config)
if self.target_profit_cache is None:
self.target_profit_cache = Cache(
self.config["user_data_dir"] / "data-nfi-profit_target_by_pair.json"
)
# If the cached data hasn't changed, it's a no-op
self.target_profit_cache.save()
def get_hold_trades_config_file(self):
proper_holds_file_path = self.config["user_data_dir"].resolve() / "nfi-hold-trades.json"
if proper_holds_file_path.is_file():
return proper_holds_file_path
strat_file_path = pathlib.Path(__file__)
hold_trades_config_file_resolve = strat_file_path.resolve().parent / "hold-trades.json"
if hold_trades_config_file_resolve.is_file():
log.warning(
"Please move %s to %s which is now the expected path for the holds file",
hold_trades_config_file_resolve,
proper_holds_file_path,
)
return hold_trades_config_file_resolve
# The resolved path does not exist, is it a symlink?
hold_trades_config_file_absolute = strat_file_path.absolute().parent / "hold-trades.json"
if hold_trades_config_file_absolute.is_file():
log.warning(
"Please move %s to %s which is now the expected path for the holds file",
hold_trades_config_file_absolute,
proper_holds_file_path,
)
return hold_trades_config_file_absolute
def load_hold_trades_config(self):
if self.hold_trades_cache is None:
hold_trades_config_file = self.get_hold_trades_config_file()
if hold_trades_config_file:
log.warning("Loading hold support data from %s", hold_trades_config_file)
self.hold_trades_cache = HoldsCache(hold_trades_config_file)
if self.hold_trades_cache:
self.hold_trades_cache.load()
def whitelist_tracker(self):
if sorted(self.coin_metrics['current_whitelist']) != sorted(self.dp.current_whitelist()):
log.info("Whitelist has changed...")
self.coin_metrics['top_traded_updated'] = False
self.coin_metrics['top_grossing_updated'] = False
# Update pairlist
self.coin_metrics['current_whitelist'] = self.dp.current_whitelist()
# Move up BTC for largest data footprint
self.coin_metrics['current_whitelist'].insert(0, self.coin_metrics['current_whitelist'].pop(self.coin_metrics['current_whitelist'].index(f"BTC/{self.config['stake_currency']}")))
def top_traded_list(self):
log.info("Updating top traded pairlist...")
tik = time.perf_counter()
self.coin_metrics['tt_dataframe'] = DataFrame()
# Build traded volume dataframe
for coin_pair in self.coin_metrics['current_whitelist']:
coin = coin_pair.split('/')[0]
# Get the volume for the daily informative timeframe and name the column for the coin
pair_dataframe = self.dp.get_pair_dataframe(pair=coin_pair, timeframe=self.info_timeframe_1d)
pair_dataframe.set_index('date')
if self.config['runmode'].value in ('live', 'dry_run'):
pair_dataframe = pair_dataframe.iloc[-7:,:]
# Set the date index of the self.coin_metrics['tt_dataframe'] once
if not 'date' in self.coin_metrics['tt_dataframe']:
self.coin_metrics['tt_dataframe']['date'] = pair_dataframe['date']
self.coin_metrics['tt_dataframe'].set_index('date')
# Calculate daily traded volume
pair_dataframe[coin] = pair_dataframe['volume'] * qtpylib.typical_price(pair_dataframe)
# Drop the columns we don't need
pair_dataframe.drop(columns=['open', 'high', 'low', 'close', 'volume'], inplace=True)
# Merge it in on the date key
self.coin_metrics['tt_dataframe'] = self.coin_metrics['tt_dataframe'].merge(pair_dataframe, on='date', how='left')
# Forward fill empty cells (due to different df shapes)
self.coin_metrics['tt_dataframe'].fillna(0, inplace=True)
# Store and drop date column for value sorting
pair_dates = self.coin_metrics['tt_dataframe']['date']
self.coin_metrics['tt_dataframe'].drop(columns=['date'], inplace=True)
# Build columns and top traded coins
column_names = [f"Coin #{i}" for i in range(1, self.coin_metrics['top_traded_len'] + 1)]
self.coin_metrics['tt_dataframe'][column_names] = self.coin_metrics['tt_dataframe'].apply(lambda x: x.nlargest(self.coin_metrics['top_traded_len']).index.values, axis=1, result_type='expand')
self.coin_metrics['tt_dataframe'].drop(columns=[col for col in self.coin_metrics['tt_dataframe'] if col not in column_names], inplace=True)
# Re-add stored date column
self.coin_metrics['tt_dataframe'].insert(loc = 0, column = 'date', value = pair_dates)
self.coin_metrics['tt_dataframe'].set_index('date')
self.coin_metrics['top_traded_updated'] = True
log.info("Updated top traded pairlist (tail-5):")
log.info(f"\n{self.coin_metrics['tt_dataframe'].tail(5)}")
tok = time.perf_counter()
log.info(f"Updating top traded pairlist took {tok - tik:0.4f} seconds...")
def top_grossing_list(self):
log.info("Updating top grossing pairlist...")
tik = time.perf_counter()
self.coin_metrics['tg_dataframe'] = DataFrame()
# Build grossing volume dataframe
for coin_pair in self.coin_metrics['current_whitelist']:
coin = coin_pair.split('/')[0]
# Get the volume for the daily informative timeframe and name the column for the coin
pair_dataframe = self.dp.get_pair_dataframe(pair=coin_pair, timeframe=self.info_timeframe_1d)
pair_dataframe.set_index('date')
if self.config['runmode'].value in ('live', 'dry_run'):
pair_dataframe = pair_dataframe.iloc[-7:,:]
# Set the date index of the self.coin_metrics['tg_dataframe'] once
if not 'date' in self.coin_metrics['tg_dataframe']:
self.coin_metrics['tg_dataframe']['date'] = pair_dataframe['date']
self.coin_metrics['tg_dataframe'].set_index('date')
# Calculate daily grossing rate
pair_dataframe[coin] = pair_dataframe['close'].pct_change() * 100
# Drop the columns we don't need
pair_dataframe.drop(columns=['open', 'high', 'low', 'close', 'volume'], inplace=True)
# Merge it in on the date key
self.coin_metrics['tg_dataframe'] = self.coin_metrics['tg_dataframe'].merge(pair_dataframe, on='date', how='left')
# Forward fill empty cells (due to different df shapes)
self.coin_metrics['tg_dataframe'].fillna(0, inplace=True)
self.coin_metrics['tg_dataframe'].to_html('pct_df.html')
# Store and drop date column for value sorting
pair_dates = self.coin_metrics['tg_dataframe']['date']
self.coin_metrics['tg_dataframe'].drop(columns=['date'], inplace=True)
# Build columns and top grossing coins
column_names = [f"Coin #{i}" for i in range(1, self.coin_metrics['top_grossing_len'] + 1)]
self.coin_metrics['tg_dataframe'][column_names] = self.coin_metrics['tg_dataframe'].apply(lambda x: x.nlargest(self.coin_metrics['top_grossing_len']).index.values, axis=1, result_type='expand')
self.coin_metrics['tg_dataframe'].drop(columns=[col for col in self.coin_metrics['tg_dataframe'] if col not in column_names], inplace=True)
# Re-add stored date column
self.coin_metrics['tg_dataframe'].insert(loc = 0, column = 'date', value = pair_dates)
self.coin_metrics['tg_dataframe'].set_index('date')
self.coin_metrics['top_grossing_updated'] = True
log.info("Updated top grossing pairlist (tail-5):")
log.info(f"\n{self.coin_metrics['tg_dataframe'].tail(5)}")
tok = time.perf_counter()
log.info(f"Updating top grossing pairlist took {tok - tik:0.4f} seconds...")
def is_top_coin(self, coin_pair, row_data, top_length) -> bool:
return coin_pair.split('/')[0] in row_data.loc['Coin #1':f"Coin #{top_length}"].values
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
# Coin metrics mechanism
if self.coin_metrics['top_traded_enabled'] or self.coin_metrics['top_grossing_enabled']:
self.whitelist_tracker()
if self.coin_metrics['top_traded_enabled'] and not self.coin_metrics['top_traded_updated']:
self.top_traded_list()
if self.coin_metrics['top_grossing_enabled'] and not self.coin_metrics['top_grossing_updated']:
self.top_grossing_list()
if self.config["runmode"].value not in ("live", "dry_run"):
return super().bot_loop_start(**kwargs)
if self.holdSupportEnabled:
self.load_hold_trades_config()
return super().bot_loop_start(**kwargs)
def get_ticker_indicator(self):
return int(self.timeframe[:-1])
def sell_signals(self, current_profit: float, max_profit:float, max_loss:float, last_candle, previous_candle_1, previous_candle_2, previous_candle_3, previous_candle_4, previous_candle_5, trade: 'Trade', current_time: 'datetime', buy_tag) -> tuple:
# Sell signal 1
if (last_candle['rsi_14'] > 78.0) and (last_candle['close'] > last_candle['bb20_2_upp']) and (previous_candle_1['close'] > previous_candle_1['bb20_2_upp']) and (previous_candle_2['close'] > previous_candle_2['bb20_2_upp']) and (previous_candle_3['close'] > previous_candle_3['bb20_2_upp']) and (previous_candle_4['close'] > previous_candle_4['bb20_2_upp']):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.01):
return True, 'sell_signal_1_1_1'
else:
if (current_profit > 0.01):
return True, 'sell_signal_1_2_1'
# Sell signal 2
elif (last_candle['rsi_14'] > 79.0) and (last_candle['close'] > last_candle['bb20_2_upp']) and (previous_candle_1['close'] > previous_candle_1['bb20_2_upp']) and (previous_candle_2['close'] > previous_candle_2['bb20_2_upp']):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.01):
return True, 'sell_signal_2_1_1'
else:
if (current_profit > 0.01):
return True, 'sell_signal_2_2_1'
# Sell signal 3
elif (last_candle['rsi_14'] > 82.0):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.01):
return True, 'sell_signal_3_1_1'
else:
if (current_profit > 0.01):
return True, 'sell_signal_3_2_1'
# Sell signal 4
elif (last_candle['rsi_14'] > 78.0) and (last_candle['rsi_14_1h'] > 78.0):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.01):
return True, 'sell_signal_4_1_1'
else:
if (current_profit > 0.01):
return True, 'sell_signal_4_2_1'
# Sell signal 6
elif (last_candle['close'] < last_candle['ema_200']) and (last_candle['close'] > last_candle['ema_50']) and (last_candle['rsi_14'] > 79.5):
if (current_profit > 0.01):
return True, 'sell_signal_6_1'
# Sell signal 7
elif (last_candle['rsi_14_1h'] > 80.0) and (last_candle['crossed_below_ema_12_26']):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.01):
return True, 'sell_signal_7_1_1'
else:
if (current_profit > 0.01):
return True, 'sell_signal_7_2_1'
# Sell signal 8
elif (last_candle['close'] > last_candle['bb20_2_upp_1h'] * 1.08):
if (last_candle['close'] > last_candle['ema_200']):
if (current_profit > 0.01):
return True, 'sell_signal_8_1_1'
else:
if (current_profit > 0.01):
return True, 'sell_signal_8_2_1'
return False, None
def sell_stoploss(self, current_profit: float, max_profit: float, max_loss: float, last_candle, previous_candle_1, trade: 'Trade', current_time: 'datetime') -> tuple:
if (last_candle['close'] < last_candle['ema_200']) and (last_candle['sma_200_dec_24']) and (last_candle['ema_25'] < last_candle['ema_50']) and (current_time - timedelta(minutes=1440) > trade.open_date_utc):
if (-0.12 <= current_profit < -0.08):
if (last_candle['close'] < last_candle['atr_high_thresh_1']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_1']):
return True, 'sell_stoploss_atr_1'
elif (-0.16 <= current_profit < -0.12):
if (last_candle['close'] < last_candle['atr_high_thresh_2']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_2']):
return True, 'sell_stoploss_atr_2'
elif (-0.2 <= current_profit < -0.16):
if (last_candle['close'] < last_candle['atr_high_thresh_3']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_3']):
return True, 'sell_stoploss_atr_3'
elif (current_profit < -0.2):
if (last_candle['close'] < last_candle['atr_high_thresh_4']) and (previous_candle_1['close'] > previous_candle_1['atr_high_thresh_4']):
return True, 'sell_stoploss_atr_4'
return False, None
def sell_over_main(self, current_profit: float, last_candle) -> tuple:
if last_candle['close'] > last_candle['ema_200']:
if (last_candle['moderi_96']):
if current_profit >= 0.20:
if last_candle['rsi_14'] < 30.0:
return True, 'sell_profit_o_bull_12_1'
elif (last_candle['rsi_14'] < 35.0) and (last_candle['cmf'] < -0.28) and (last_candle['rsi_14_1h'] < 35.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_12_2'
elif 0.20 > current_profit >= 0.12:
if last_candle['rsi_14'] < 32.0:
return True, 'sell_profit_o_bull_11_1'
elif (last_candle['rsi_14'] < 37.0) and (last_candle['cmf'] < -0.24) and (last_candle['rsi_14_1h'] < 37.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_11_2'
elif 0.12 > current_profit >= 0.1:
if last_candle['rsi_14'] < 40.0:
return True, 'sell_profit_o_bull_10_1'
elif (last_candle['rsi_14'] < 45.0) and (last_candle['cmf'] < -0.22) and (last_candle['rsi_14_1h'] < 43.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_10_2'
elif 0.1 > current_profit >= 0.09:
if last_candle['rsi_14'] < 50.0:
return True, 'sell_profit_o_bull_9_1'
elif (last_candle['rsi_14'] < 54.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 49.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_9_2'
elif 0.09 > current_profit >= 0.08:
if (last_candle['rsi_14'] < 49.0):
return True, 'sell_profit_o_bull_8_1'
elif (last_candle['rsi_14'] < 53.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 49.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_8_2'
elif 0.08 > current_profit >= 0.07:
if (last_candle['rsi_14'] < 48.0):
return True, 'sell_profit_o_bull_7_1'
elif (last_candle['rsi_14'] < 52.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 49.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_7_2'
elif 0.07 > current_profit >= 0.06:
if (last_candle['rsi_14'] < 46.0):
return True, 'sell_profit_o_bull_6_1'
elif (last_candle['rsi_14'] < 51.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 49.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_6_2'
elif 0.06 > current_profit >= 0.05:
if (last_candle['rsi_14'] < 44.0):
return True, 'sell_profit_o_bull_5_1'
elif (last_candle['rsi_14'] < 49.0) and (last_candle['cmf'] < -0.13) and (last_candle['rsi_14_1h'] < 49.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_5_2'
elif 0.05 > current_profit >= 0.04:
if (last_candle['rsi_14'] < 42.0):
return True, 'sell_profit_o_bull_4_1'
elif (last_candle['rsi_14'] < 47.0) and (last_candle['cmf'] < -0.14) and (last_candle['rsi_14_1h'] < 48.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_4_2'
elif 0.04 > current_profit >= 0.03:
if (last_candle['rsi_14'] < 38.0):
return True, 'sell_profit_o_bull_3_1'
elif (last_candle['rsi_14'] < 43.0) and (last_candle['cmf'] < -0.15) and (last_candle['rsi_14_1h'] < 47.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_3_2'
elif 0.03 > current_profit >= 0.02:
if (last_candle['rsi_14'] < 34.0):
return True, 'sell_profit_o_bull_2_1'
elif (last_candle['rsi_14'] < 39.0) and (last_candle['cmf'] < -0.16) and (last_candle['rsi_14_1h'] < 46.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_2_2'
elif 0.02 > current_profit >= 0.012:
if (last_candle['rsi_14'] < 32.0):
return True, 'sell_profit_o_bull_1_1'
elif (last_candle['rsi_14'] < 37.0) and (last_candle['cmf'] < -0.2) and (last_candle['rsi_14_1h'] < 44.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bull_1_2'
else:
if current_profit >= 0.20:
if last_candle['rsi_14'] < 31.0:
return True, 'sell_profit_o_bear_12_1'
elif (last_candle['rsi_14'] < 36.0) and (last_candle['cmf'] < -0.28) and (last_candle['rsi_14_1h'] < 36.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_12_2'
elif 0.20 > current_profit >= 0.12:
if last_candle['rsi_14'] < 33.0:
return True, 'sell_profit_o_bear_11_1'
elif (last_candle['rsi_14'] < 38.0) and (last_candle['cmf'] < -0.24) and (last_candle['rsi_14_1h'] < 38.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_11_2'
elif 0.12 > current_profit >= 0.10:
if last_candle['rsi_14'] < 41.0:
return True, 'sell_profit_o_bear_10_1'
elif (last_candle['rsi_14'] < 46.0) and (last_candle['cmf'] < -0.22) and (last_candle['rsi_14_1h'] < 44.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_10_2'
elif 0.10 > current_profit >= 0.09:
if last_candle['rsi_14'] < 51.0:
return True, 'sell_profit_o_bear_9_1'
elif (last_candle['rsi_14'] < 57.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_9_2'
elif 0.09 > current_profit >= 0.08:
if (last_candle['rsi_14'] < 50.0):
return True, 'sell_profit_o_bear_8_1'
elif (last_candle['rsi_14'] < 56.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_8_2'
elif 0.08 > current_profit >= 0.07:
if (last_candle['rsi_14'] < 49.0):
return True, 'sell_profit_o_bear_7_1'
elif (last_candle['rsi_14'] < 55.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_7_2'
elif 0.07 > current_profit >= 0.06:
if (last_candle['rsi_14'] < 47.0):
return True, 'sell_profit_o_bear_6_1'
elif (last_candle['rsi_14'] < 54.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_6_2'
elif 0.06 > current_profit >= 0.05:
if (last_candle['rsi_14'] < 45.0):
return True, 'sell_profit_o_bear_5_1'
elif (last_candle['rsi_14'] < 53.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_5_2'
elif 0.05 > current_profit >= 0.04:
if (last_candle['rsi_14'] < 43.0):
return True, 'sell_profit_o_bear_4_1'
elif (last_candle['rsi_14'] < 52.0) and (last_candle['cmf'] < -0.13) and (last_candle['rsi_14_1h'] < 49.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_4_2'
elif 0.04 > current_profit >= 0.03:
if (last_candle['rsi_14'] < 39.0):
return True, 'sell_profit_o_bear_3_1'
elif (last_candle['rsi_14'] < 51.0) and (last_candle['cmf'] < -0.14) and (last_candle['rsi_14_1h'] < 48.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_3_2'
elif 0.03 > current_profit >= 0.02:
if (last_candle['rsi_14'] < 35.0):
return True, 'sell_profit_o_bear_2_1'
elif (last_candle['rsi_14'] < 50.0) and (last_candle['cmf'] < -0.15) and (last_candle['rsi_14_1h'] < 47.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_2_2'
elif 0.02 > current_profit >= 0.012:
if (last_candle['rsi_14'] < 33.0):
return True, 'sell_profit_o_bear_1_1'
elif (last_candle['rsi_14'] < 38.0) and (last_candle['cmf'] < -0.2) and (last_candle['rsi_14_1h'] < 45.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_1_2'
return False, None
def sell_under_main(self, current_profit: float, last_candle) -> tuple:
if last_candle['close'] < last_candle['ema_200']:
if (last_candle['moderi_96']):
if current_profit >= 0.20:
if last_candle['rsi_14'] < 31.0:
return True, 'signal_profit_u_bull_12_1'
elif (last_candle['rsi_14'] < 32.0) and (last_candle['cmf'] < -0.28) and (last_candle['rsi_14_1h'] < 36.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_12_2'
elif 0.20 > current_profit >= 0.12:
if last_candle['rsi_14'] < 33.0:
return True, 'sell_profit_u_bull_11_1'
elif (last_candle['rsi_14'] < 38.0) and (last_candle['cmf'] < -0.24) and (last_candle['rsi_14_1h'] < 38.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_11_2'
elif 0.12 > current_profit >= 0.10:
if last_candle['rsi_14'] < 41.0:
return True, 'sell_profit_u_bull_10_1'
elif (last_candle['rsi_14'] < 46.0) and (last_candle['cmf'] < -0.22) and (last_candle['rsi_14_1h'] < 44.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_10_2'
elif 0.10 > current_profit >= 0.09:
if last_candle['rsi_14'] < 51.0:
return True, 'sell_profit_u_bull_9_1'
elif (last_candle['rsi_14'] < 55.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_9_2'
elif 0.09 > current_profit >= 0.08:
if last_candle['rsi_14'] < 50.0:
return True, 'sell_profit_u_bull_8_1'
elif (last_candle['rsi_14'] < 54.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_8_2'
elif 0.08 > current_profit >= 0.07:
if last_candle['rsi_14'] < 49.0:
return True, 'sell_profit_u_bull_7_1'
elif (last_candle['rsi_14'] < 53.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_7_2'
elif 0.07 > current_profit >= 0.06:
if last_candle['rsi_14'] < 47.0:
return True, 'sell_profit_u_bull_6_1'
elif (last_candle['rsi_14'] < 52.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_6_2'
elif 0.06 > current_profit >= 0.05:
if last_candle['rsi_14'] < 45.0:
return True, 'sell_profit_u_bull_5_1'
elif (last_candle['rsi_14'] < 50.0) and (last_candle['cmf'] < -0.13) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_5_2'
elif 0.05 > current_profit >= 0.04:
if last_candle['rsi_14'] < 43.0:
return True, 'sell_profit_u_bull_4_1'
elif (last_candle['rsi_14'] < 48.0) and (last_candle['cmf'] < -0.14) and (last_candle['rsi_14_1h'] < 49.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_4_2'
elif 0.04 > current_profit >= 0.03:
if last_candle['rsi_14'] < 39.0:
return True, 'sell_profit_u_bull_3_1'
elif (last_candle['rsi_14'] < 44.0) and (last_candle['cmf'] < -0.15) and (last_candle['rsi_14_1h'] < 48.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_3_2'
elif 0.03 > current_profit >= 0.02:
if last_candle['rsi_14'] < 35.0:
return True, 'sell_profit_u_bull_2_1'
elif (last_candle['rsi_14'] < 40.0) and (last_candle['cmf'] < -0.16) and (last_candle['rsi_14_1h'] < 47.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_2_2'
elif 0.02 > current_profit >= 0.01:
if (last_candle['rsi_14'] < 33.0):
return True, 'sell_profit_u_bull_1_1'
elif (last_candle['rsi_14'] < 38.0) and (last_candle['cmf'] < -0.2) and (last_candle['rsi_14_1h'] < 45.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bull_1_2'
else:
if current_profit >= 0.20:
if last_candle['rsi_14'] < 32.0:
return True, 'sell_profit_u_bear_12_1'
elif (last_candle['rsi_14'] < 37.0) and (last_candle['cmf'] < -0.28) and (last_candle['rsi_14_1h'] < 37.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bear_12_2'
elif 0.20 > current_profit >= 0.12:
if last_candle['rsi_14'] < 34.0:
return True, 'sell_profit_u_bear_11_1'
elif (last_candle['rsi_14'] < 39.0) and (last_candle['cmf'] < -0.24) and (last_candle['rsi_14_1h'] < 39.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bear_11_2'
elif 0.12 > current_profit >= 0.10:
if last_candle['rsi_14'] < 42.0:
return True, 'sell_profit_u_bear_10_1'
elif (last_candle['rsi_14'] < 47.0) and (last_candle['cmf'] < -0.22) and (last_candle['rsi_14_1h'] < 45.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bear_10_2'
elif 0.10 > current_profit >= 0.09:
if last_candle['rsi_14'] < 54.0:
return True, 'sell_profit_u_bear_9_1'
elif (last_candle['rsi_14'] < 58.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 51.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_o_bear_9_2'
elif 0.09 > current_profit >= 0.08:
if last_candle['rsi_14'] < 52.0:
return True, 'sell_profit_u_bear_8_1'
elif (last_candle['rsi_14'] < 57.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 51.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bear_8_2'
elif 0.08 > current_profit >= 0.07:
if last_candle['rsi_14'] < 50.0:
return True, 'sell_profit_u_bear_7_1'
elif (last_candle['rsi_14'] < 56.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 51.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bear_7_2'
elif 0.07 > current_profit >= 0.06:
if last_candle['rsi_14'] < 48.0:
return True, 'sell_profit_u_bear_6_1'
elif (last_candle['rsi_14'] < 55.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 51.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bear_6_2'
elif 0.06 > current_profit >= 0.05:
if last_candle['rsi_14'] < 46.0:
return True, 'sell_profit_u_bear_5_1'
elif (last_candle['rsi_14'] < 54.0) and (last_candle['cmf'] < -0.12) and (last_candle['rsi_14_1h'] < 51.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):
return True, 'sell_profit_u_bear_5_2'
elif 0.05 > current_profit >= 0.04:
if last_candle['rsi_14'] < 44.0:
return True, 'sell_profit_u_bear_4_1'
elif (last_candle['rsi_14'] < 53.0) and (last_candle['cmf'] < -0.13) and (last_candle['rsi_14_1h'] < 50.0) and (last_candle['ema_12'] < last_candle['ema_26']) and (last_candle['ema_25'] < last_candle['ema_50']):