Merge dfdb58edff into 208d3770da

config.json.example

@@ -10,6 +10,12 @@
         "20":  0.02,
         "0":  0.04
     },
+    "trailing_stoploss": {
+        "40":  0.0,
+        "30":  0.01,
+        "20":  0.02,
+        "0":  0.04
+    },
     "stoploss": -0.10,
     "bid_strategy": {
         "ask_last_balance": 0.0

freqtrade/analyze.py

@@ -88,6 +88,7 @@ def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
             (dataframe['plus_di'] > 0.5)
         ),
         'buy'] = 1
+    dataframe['buy'] = 1
 
     return dataframe
 

freqtrade/main.py

@@ -177,6 +177,23 @@ def min_roi_reached(trade: Trade, current_rate: float, current_time: datetime) -
         logger.debug('Stop loss hit.')
         return True
 
+    # Check if profit is positive, time matches and current rate is below trailing stop loss
+    if current_profit > 0 and 'trailing_stoploss' in _CONF:
+        logger.debug('Check trailing stop loss...')
+        time_diff = (current_time - trade.open_date).total_seconds() / 60
+        for duration, threshold in sorted(_CONF['trailing_stoploss'].items()):
+            if time_diff > float(duration):
+                percentage_change = ((current_rate - trade.stat_max_rate) / trade.stat_max_rate) 
+                logger.debug('Check trailing stop loss. %s < %s' % (percentage_change, -threshold))
+                if percentage_change < -threshold:
+                    logger.debug('Trailing stop loss hit: %s, %s : %s < %s' % \
+                                                        (duration, 
+                                                         threshold, 
+                                                         percentage_change, 
+                                                         -threshold)
+                                )
+                    return True
+
     # Check if time matches and current rate is above threshold
     time_diff = (current_time - trade.open_date).total_seconds() / 60
     for duration, threshold in sorted(_CONF['minimal_roi'].items()):
@@ -197,7 +214,13 @@ def handle_trade(trade: Trade) -> bool:
 
     logger.debug('Handling %s ...', trade)
     current_rate = exchange.get_ticker(trade.pair)['bid']
+    
+    # Update statistic values for trailing stoploss
+    trade.update_stats(current_rate)
 
+    # Update statistic values for trailing stoploss
+    trade.update_stats(current_rate)
+    
     # Check if minimal roi has been reached
     if min_roi_reached(trade, current_rate, datetime.utcnow()):
         logger.debug('Executing sell due to ROI ...')
@@ -356,7 +379,7 @@ def main() -> None:
 
     # Initialize logger
     logging.basicConfig(
-        level=args.loglevel,
+        level=args.loglevel,#'DEBUG',#args.loglevel,
         format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
     )
 

freqtrade/misc.py

@@ -217,6 +217,13 @@ CONF_SCHEMA = {
             },
             'minProperties': 1
         },
+        'trailing_stoploss': {
+            'type': 'object',
+            'patternProperties': {
+                '^[0-9.]+$': {'type': 'number'}
+            },
+            'minProperties': 0
+        },
         'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True},
         'bid_strategy': {
             'type': 'object',

freqtrade/optimize/backtesting.py

@@ -98,6 +98,7 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
                 trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
 
             trade = Trade(
+                pair=pair,
                 open_rate=row.close,
                 open_date=row.date,
                 stake_amount=stake_amount,
@@ -107,6 +108,10 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
 
             # calculate win/lose forwards from buy point
             for row2 in ticker[row.Index + 1:].itertuples(index=True):
+                
+                # Update statistic values for trailing stoploss
+                trade.update_stats(row2.close)
+                
                 if max_open_trades > 0:
                     # Increase trade_count_lock for every iteration
                     trade_count_lock[row2.date] = trade_count_lock.get(row2.date, 0) + 1

freqtrade/persistence.py

@@ -71,6 +71,10 @@ class Trade(_DECL_BASE):
     open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
     close_date = Column(DateTime)
     open_order_id = Column(String)
+    stat_min_rate = Column(Float)
+    stat_min_rate_date = Column(DateTime)
+    stat_max_rate = Column(Float)
+    stat_max_rate_date = Column(DateTime)
 
     def __repr__(self):
         return 'Trade(id={}, pair={}, amount={:.8f}, open_rate={:.8f}, open_since={})'.format(
@@ -78,9 +82,26 @@ class Trade(_DECL_BASE):
             self.pair,
             self.amount,
             self.open_rate,
-            arrow.get(self.open_date).humanize() if self.is_open else 'closed'
+            arrow.get(self.open_date).humanize() if self.is_open else 'closed',
+            self.stat_min_rate,
+            self.stat_max_rate,
         )
 
+    def update_stats(self, current_rate: Dict) -> None:
+        """
+        Updates this entity statistics with current rates.
+        :param current_rate: current rate retrieved by exchange.get_ticker()
+        :return: None
+        """
+        if not self.stat_min_rate or current_rate < self.stat_min_rate:
+            logger.debug('Update stat_min_rate. %s -> %s' % (self.stat_min_rate, current_rate))
+            self.stat_min_rate = current_rate
+            self.stat_min_rate_date = datetime.utcnow()
+        if not self.stat_max_rate or current_rate > self.stat_max_rate:
+            logger.debug('Update stat_max_rate. %s -> %s' % (self.stat_max_rate, current_rate))
+            self.stat_max_rate = current_rate
+            self.stat_max_rate_date = datetime.utcnow()
+
     def update(self, order: Dict) -> None:
         """
         Updates this entity with amount and actual open/close rates.