sell last rebuy with trailing stop loss

NostalgiaForInfinityX.py

@@ -15,6 +15,7 @@
 from typing import Dict
 from freqtrade.persistence import Trade
 from datetime import datetime, timedelta
+from decimal import Decimal
 from technical.util import resample_to_interval, resampled_merge
 from technical.indicators import RMI, zema, VIDYA, ichimoku
 import time
@@ -110,7 +111,7 @@ class NostalgiaForInfinityX(IStrategy):
     INTERFACE_VERSION = 2
 
     def version(self) -> str:
-        return "v11.0.269"
+        return "v11.0.270"
 
     # ROI table:
     minimal_roi = {
@@ -127,6 +128,8 @@ def version(self) -> str:
 
     use_custom_stoploss = False
 
+    custom_info = {}
+
     # Optimal timeframe for the strategy.
     timeframe = '5m'
     res_timeframe = 'none'
@@ -2293,6 +2296,10 @@ def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: f
         else:
             return proposed_stake
 
+    def calc_profit_ratio2(self, open_rate: float, current_rate: float, trade: Trade) ->float:
+        return  float(( Decimal(1-trade.fee_close)* Decimal(current_rate) )/
+            (Decimal(1+trade.fee_open)* Decimal(open_rate) )-1)
+
     def adjust_trade_position(self, trade: Trade, current_time: datetime,
                               current_rate: float, current_profit: float, min_stake: float,
                               max_stake: float, **kwargs):
@@ -2317,6 +2324,21 @@ def adjust_trade_position(self, trade: Trade, current_time: datetime,
         if (self.position_adjustment_enable == False) or (current_profit > -0.03):
             return None
 
+        filled_buys = trade.select_filled_orders('buy')
+        count_of_buys = len(filled_buys)
+        max_profit2=self.custom_info.get(trade.pair,0)
+        last_buy_order = filled_buys[-1]
+        last_open_rate = last_buy_order.average or last_buy_order.price
+        current_profit2=self.calc_profit_ratio2(last_open_rate, current_rate, trade)
+        # if current_time.second %10 == 0: log.info('partial_sell ' + ', '.join(map(str,(trade.pair, max_profit2, current_profit2, last_open_rate, current_rate))))
+        if max_profit2<current_profit2: self.custom_info[trade.pair]=current_profit2
+        if max_profit2-current_profit2>.005-0.0025*(count_of_buys-2) and current_profit2 > 0 and count_of_buys > 1:
+            self.custom_info[trade.pair]=0
+            last_stake_amt=last_buy_order.amount
+            return -last_stake_amt
+
+        if count_of_buys > self.max_rebuy_orders and self.dp.runmode.value not in ('backtest','dry_run'):
+            return
         dataframe, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
         last_candle = dataframe.iloc[-1].squeeze()
         previous_candle = dataframe.iloc[-2].squeeze()
@@ -2328,20 +2350,17 @@ def adjust_trade_position(self, trade: Trade, current_time: datetime,
         ):
             return None
 
-        filled_buys = trade.select_filled_orders('buy')
-        count_of_buys = len(filled_buys)
-
         if (count_of_buys == 1):
             if (
-                    (current_profit > -0.08)
+                    (current_profit > -0.03)
                     or (
                         (last_candle['crsi'] < 12.0)
                     )
             ):
                 return None
         elif (count_of_buys == 2):
             if (
-                    (current_profit > -0.14)
+                    (current_profit > -0.04)
                     or (
                         (last_candle['crsi'] < 20.0)
                         or (last_candle['crsi_1h'] < 11.0)
@@ -2362,17 +2381,18 @@ def adjust_trade_position(self, trade: Trade, current_time: datetime,
         # Log if the last candle triggered a buy signal, even if max rebuys reached
         if last_candle['buy'] == 1 and self.dp.runmode.value in ('backtest','dry_run'):
             log.info(f"Rebuy: a buy tag found for pair {trade.pair}")
+            if count_of_buys > self.max_rebuy_orders:
+                return
 
         # Maximum 2 rebuys. Half the stake of the original.
-        if 0 < count_of_buys <= self.max_rebuy_orders:
-            try:
-                # This returns first order stake size
-                stake_amount = filled_buys[0].cost
-                # This then calculates current safety order size
-                stake_amount = stake_amount * (0.35 + (count_of_buys * 0.005))
-                return stake_amount
-            except Exception as exception:
-                return None
+        try:
+            # This returns first order stake size
+            stake_amount = filled_buys[0].cost
+            # This then calculates current safety order size
+            stake_amount = stake_amount * (0.35 + (count_of_buys * 0.005))
+            return stake_amount
+        except Exception as exception:
+            return None
 
         return None