Merge pull request #11656 from mrpabloyeah/add-custom-roi-strategy-callback

Add custom_roi() strategy callback

docs/strategy-callbacks.md

@@ -12,6 +12,7 @@ Currently available callbacks:
 * [`custom_stake_amount()`](#stake-size-management)
 * [`custom_exit()`](#custom-exit-signal)
 * [`custom_stoploss()`](#custom-stoploss)
+* [`custom_roi()`](#custom-roi)
 * [`custom_entry_price()` and `custom_exit_price()`](#custom-order-price-rules)
 * [`check_entry_timeout()` and `check_exit_timeout()`](#custom-order-timeout-rules)
 * [`confirm_trade_entry()`](#trade-entry-buy-order-confirmation)
@@ -499,6 +500,135 @@ The helper function `stoploss_from_absolute()` can be used to convert from an ab
 
 ---
 
+## Custom ROI
+
+Called for open trade every iteration (roughly every 5 seconds) until a trade is closed.
+
+The usage of the custom ROI method must be enabled by setting `use_custom_roi=True` on the strategy object.
+
+This method allows you to define a custom minimum ROI threshold for exiting a trade, expressed as a ratio (e.g., `0.05` for 5% profit). If both `minimal_roi` and `custom_roi` are defined, the lower of the two thresholds will trigger an exit. For example, if `minimal_roi` is set to `{"0": 0.10}` (10% at 0 minutes) and `custom_roi` returns `0.05`, the trade will exit when the profit reaches 5%. Also, if `custom_roi` returns `0.10` and `minimal_roi` is set to `{"0": 0.05}` (5% at 0 minutes), the trade will be closed when the profit reaches 5%.
+
+The method must return a float representing the new ROI threshold as a ratio, or `None` to fall back to the `minimal_roi` logic. Returning `NaN` or `inf` values is considered invalid and will be treated as `None`, causing the bot to use the `minimal_roi` configuration.
+
+### Custom ROI examples
+
+The following examples illustrate how to use the `custom_roi` function to implement different ROI logics.
+
+#### Custom ROI per side
+
+Use different ROI thresholds depending on the `side`. In this example, 5% for long entries and 2% for short entries.
+
+```python
+# Default imports
+
+class AwesomeStrategy(IStrategy):
+
+    use_custom_roi = True
+
+    # ... populate_* methods
+
+    def custom_roi(self, pair: str, trade: Trade, current_time: datetime, trade_duration: int,
+                   entry_tag: str | None, side: str, **kwargs) -> float | None:
+        """
+        Custom ROI logic, returns a new minimum ROI threshold (as a ratio, e.g., 0.05 for +5%).
+        Only called when use_custom_roi is set to True.
+
+        If used at the same time as minimal_roi, an exit will be triggered when the lower
+        threshold is reached. Example: If minimal_roi = {"0": 0.01} and custom_roi returns 0.05,
+        an exit will be triggered if profit reaches 5%.
+
+        :param pair: Pair that's currently analyzed.
+        :param trade: trade object.
+        :param current_time: datetime object, containing the current datetime.
+        :param trade_duration: Current trade duration in minutes.
+        :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+        :param side: 'long' or 'short' - indicating the direction of the current trade.
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return float: New ROI value as a ratio, or None to fall back to minimal_roi logic.
+        """
+        return 0.05 if side == "long" else 0.02
+```
+
+#### Custom ROI per pair
+
+Use different ROI thresholds depending on the `pair`.
+
+```python
+# Default imports
+
+class AwesomeStrategy(IStrategy):
+
+    use_custom_roi = True
+
+    # ... populate_* methods
+
+    def custom_roi(self, pair: str, trade: Trade, current_time: datetime, trade_duration: int,
+                   entry_tag: str | None, side: str, **kwargs) -> float | None:
+
+        stake = trade.stake_currency
+        roi_map = {
+            f"BTC/{stake}": 0.02, # 2% for BTC
+            f"ETH/{stake}": 0.03, # 3% for ETH
+            f"XRP/{stake}": 0.04, # 4% for XRP
+        }
+
+        return roi_map.get(pair, 0.01) # 1% for any other pair
+```
+
+#### Custom ROI per entry tag
+
+Use different ROI thresholds depending on the `entry_tag` provided with the buy signal.
+
+```python
+# Default imports
+
+class AwesomeStrategy(IStrategy):
+
+    use_custom_roi = True
+
+    # ... populate_* methods
+
+    def custom_roi(self, pair: str, trade: Trade, current_time: datetime, trade_duration: int,
+                   entry_tag: str | None, side: str, **kwargs) -> float | None:
+
+        roi_by_tag = {
+            "breakout": 0.08,       # 8% if tag is "breakout"
+            "rsi_overbought": 0.05, # 5% if tag is "rsi_overbought"
+            "mean_reversion": 0.03, # 3% if tag is "mean_reversion"
+        }
+
+        return roi_by_tag.get(entry_tag, 0.01)  # 1% if tag is unknown
+```
+
+#### Custom ROI based on ATR
+
+ROI value may be derived from indicators stored in dataframe. This example uses the ATR ratio as ROI.
+
+``` python
+# Default imports
+# <...>
+import talib.abstract as ta
+
+class AwesomeStrategy(IStrategy):
+
+    use_custom_roi = True
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # <...>
+        dataframe["atr"] = ta.ATR(dataframe, timeperiod=10)
+
+    def custom_roi(self, pair: str, trade: Trade, current_time: datetime, trade_duration: int,
+                   entry_tag: str | None, side: str, **kwargs) -> float | None:
+
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+        atr_ratio = last_candle["atr"] / last_candle["close"]
+
+        return atr_ratio # Returns the ATR value as ratio
+```
+
+---
+
 ## Custom order price rules
 
 By default, freqtrade use the orderbook to automatically set an order price([Relevant documentation](configuration.md#prices-used-for-orders)), you also have the option to create custom order prices based on your strategy.