docs: Update "tag" examples with advanced examples

docs/strategy-advanced.md

@@ -174,17 +174,27 @@ class AwesomeStrategy(IStrategy):
 
 ## Enter Tag
 
-When your strategy has multiple buy signals, you can name the signal that triggered.
-Then you can access your buy signal on `custom_exit`
+When your strategy has multiple entry signals, you can name the signal that triggered.
+Then you can access your entry signal on `custom_exit`
 
 ```python
 def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    dataframe["enter_tag"] = ""
+    signal_rsi = (qtpylib.crossed_above(dataframe["rsi"], 35))
+    signal_bblower = (dataframe["bb_lowerband"] < dataframe["close"])
+    # Additional conditions
     dataframe.loc[
         (
-            (dataframe['rsi'] < 35) &
-            (dataframe['volume'] > 0)
-        ),
-        ['enter_long', 'enter_tag']] = (1, 'buy_signal_rsi')
+            signal_rsi
+            | signal_bblower
+            # ... additional signals to enter a long position
+        )
+        & (dataframe["volume"] > 0)
+            , "enter_long"
+        ] = 1
+    # Concatenate the tags so all signals are kept
+    dataframe.loc[signal_rsi, "enter_tag"] += "long_signal_rsi "
+    dataframe.loc[signal_bblower, "enter_tag"] += "long_signal_bblower "
 
     return dataframe
 
@@ -192,8 +202,11 @@ def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_r
                 current_profit: float, **kwargs):
     dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
     last_candle = dataframe.iloc[-1].squeeze()
-    if trade.enter_tag == 'buy_signal_rsi' and last_candle['rsi'] > 80:
-        return 'sell_signal_rsi'
+    if "long_signal_rsi" in trade.enter_tag and last_candle["rsi"] > 80:
+        return "exit_signal_rsi"
+    if "long_signal_bblower" in trade.enter_tag and last_candle["high"] > last_candle["bb_upperband"]:
+        return "exit_signal_bblower"
+    # ...
     return None
 
 ```
@@ -213,17 +226,27 @@ Similar to [Entry Tagging](#enter-tag), you can also specify an exit tag.
 
 ``` python
 def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    dataframe["exit_tag"] = ""
+    rsi_exit_signal = (dataframe["rsi"] > 70)
+    ema_exit_signal  = (dataframe["ema20"] < dataframe["ema50"])
+    # Additional conditions
     dataframe.loc[
         (
-            (dataframe['rsi'] > 70) &
-            (dataframe['volume'] > 0)
-        ),
-        ['exit_long', 'exit_tag']] = (1, 'exit_rsi')
+            rsi_exit_signal
+            | ema_exit_signal
+            # ... additional signals to exit a long position
+        ) &
+        (dataframe["volume"] > 0)
+        ,
+    "exit_long"] = 1
+    # Concatenate the tags so all signals are kept
+    dataframe.loc[rsi_exit_signal, "exit_tag"] += "exit_signal_rsi "
+    dataframe.loc[rsi_exit_signal2, "exit_tag"] += "exit_signal_rsi "
 
     return dataframe
 ```
 
-The provided exit-tag is then used as sell-reason - and shown as such in backtest results.
+The provided exit-tag is then used as exit-reason - and shown as such in backtest results.
 
 !!! Note
     `exit_reason` is limited to 100 characters, remaining data will be truncated.