Add ProfitDrawdownHyperoptLoss method

docs/hyperopt.md

@@ -116,7 +116,7 @@ optional arguments:
                         ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss,
                         SharpeHyperOptLoss, SharpeHyperOptLossDaily,
                         SortinoHyperOptLoss, SortinoHyperOptLossDaily,
-                        CalmarHyperOptLoss, MaxDrawDownHyperOptLoss
+                        CalmarHyperOptLoss, MaxDrawDownHyperOptLoss, ProfitDrawDownHyperOptLoss
   --disable-param-export
                         Disable automatic hyperopt parameter export.
   --ignore-missing-spaces, --ignore-unparameterized-spaces
@@ -525,6 +525,7 @@ Currently, the following loss functions are builtin:
 * `SortinoHyperOptLossDaily` - optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation.
 * `MaxDrawDownHyperOptLoss` - Optimizes Maximum drawdown.
 * `CalmarHyperOptLoss` - Optimizes Calmar Ratio calculated on trade returns relative to max drawdown.
+* `ProfitDrawDownHyperOptLoss` - Optimizes by max Profit & min Drawdown objective. `DRAWDOWN_MULT` variable within the hyperoptloss file can be adjusted to be stricter or more flexible on drawdown purposes.
 
 Creation of a custom loss function is covered in the [Advanced Hyperopt](advanced-hyperopt.md) part of the documentation.
 

freqtrade/constants.py

@@ -26,7 +26,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
                          'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
                          'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily',
                          'CalmarHyperOptLoss',
-                         'MaxDrawDownHyperOptLoss']
+                         'MaxDrawDownHyperOptLoss', 'ProfitDrawDownHyperOptLoss']
 AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
                        'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
                        'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',

freqtrade/optimize/hyperopt_loss_profit_drawdown.py

@@ -0,0 +1,29 @@
+"""
+ProfitDrawDownHyperOptLoss
+
+This module defines the alternative HyperOptLoss class based on Profit &
+Drawdown objective which can be used for Hyperoptimization.
+
+Possible to change `DRAWDOWN_MULT` to penalize drawdown objective for
+individual needs.
+"""
+from pandas import DataFrame
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+from freqtrade.data.btanalysis import calculate_max_drawdown
+
+# higher numbers penalize drawdowns more severely
+DRAWDOWN_MULT = 0.075
+
+
+class ProfitDrawDownHyperOptLoss(IHyperOptLoss):
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int, *args, **kwargs) -> float:
+        total_profit = results["profit_abs"].sum()
+
+        # from freqtrade.optimize.optimize_reports.generate_strategy_stats()
+        try:
+            _, _, _, _, max_drawdown_per = calculate_max_drawdown(results, value_col="profit_ratio")
+        except ValueError:
+            max_drawdown_per = 0
+
+        return -1 * (total_profit * (1 - max_drawdown_per * DRAWDOWN_MULT))

tests/optimize/test_hyperoptloss.py

@@ -86,6 +86,7 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
     "SharpeHyperOptLossDaily",
     "MaxDrawDownHyperOptLoss",
     "CalmarHyperOptLoss",
+    "ProfitDrawDownHyperOptLoss",
 
 ])
 def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunction) -> None:
@@ -106,7 +107,7 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
         config=default_conf,
         processed=None,
         backtest_stats={'profit_total': hyperopt_results['profit_abs'].sum()}
-        )
+    )
     over = hl.hyperopt_loss_function(
         results_over,
         trade_count=len(results_over),