Complete the integration on freqtrade

docs/commands/hyperopt.md

@@ -79,6 +79,7 @@ options:
                         SortinoHyperOptLoss, SortinoHyperOptLossDaily,
                         CalmarHyperOptLoss, MaxDrawDownHyperOptLoss,
                         MaxDrawDownRelativeHyperOptLoss,
+                        MaxDrawDownPerPairHyperOptLoss,
                         ProfitDrawDownHyperOptLoss, MultiMetricHyperOptLoss
   --disable-param-export
                         Disable automatic hyperopt parameter export.

docs/hyperopt.md

@@ -471,6 +471,7 @@ Currently, the following loss functions are builtin:
 * `SortinoHyperOptLossDaily` - optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation.
 * `MaxDrawDownHyperOptLoss` - Optimizes Maximum absolute drawdown.
 * `MaxDrawDownRelativeHyperOptLoss` -  Optimizes both maximum absolute drawdown while also adjusting for maximum relative drawdown.
+* `MaxDrawDownPerPairHyperOptLoss` -  Optimizes the profit/drawdown ratio calculated individually for each pair in the pairlist.
 * `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.
 * `MultiMetricHyperOptLoss` -  Optimizes by several key metrics to achieve balanced performance. The primary focus is on maximizing Profit and minimizing Drawdown, while also considering additional metrics such as Profit Factor, Expectancy Ratio and Winrate. Moreover, it applies a penalty for epochs with a low number of trades, encouraging strategies with adequate trade frequency.

tests/optimize/test_hyperoptloss.py

@@ -153,6 +153,7 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
         "SharpeHyperOptLossDaily",
         "MaxDrawDownHyperOptLoss",
         "MaxDrawDownRelativeHyperOptLoss",
+        "MaxDrawDownPerPairHyperOptLoss",
         "CalmarHyperOptLoss",
         "ProfitDrawDownHyperOptLoss",
         "MultiMetricHyperOptLoss",
@@ -165,6 +166,42 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
     results_under = hyperopt_results.copy()
     results_under["profit_abs"] = hyperopt_results["profit_abs"] / 2 - 0.2
     results_under["profit_ratio"] = hyperopt_results["profit_ratio"] / 2
+    pair_results = [
+        {
+            "key": "ETH/USDT",
+            "max_drawdown_abs": 50.0,
+            "profit_total_abs": 100.0,
+        },
+        {
+            "key": "BTC/USDT",
+            "max_drawdown_abs": 50.0,
+            "profit_total_abs": 100.0,
+        }
+    ]
+    pair_results_over = [
+        {
+            "key": "ETH/USDT",
+            "max_drawdown_abs": 25.0,
+            "profit_total_abs": 200.0,
+        },
+        {
+            "key": "BTC/USDT",
+            "max_drawdown_abs": 25.0,
+            "profit_total_abs": 200.0,
+        }
+    ]
+    pair_results_under = [
+        {
+            "key": "ETH/USDT",
+            "max_drawdown_abs": 100.0,
+            "profit_total_abs": 50.0,
+        },
+        {
+            "key": "BTC/USDT",
+            "max_drawdown_abs": 100.0,
+            "profit_total_abs": 50.0,
+        }
+    ]
 
     default_conf.update({"hyperopt_loss": lossfunction})
     hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
@@ -175,7 +212,10 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
         max_date=datetime(2019, 5, 1),
         config=default_conf,
         processed=None,
-        backtest_stats={"profit_total": hyperopt_results["profit_abs"].sum()},
+        backtest_stats={
+            "profit_total": hyperopt_results["profit_abs"].sum(),
+            "results_per_pair": pair_results,
+        },
         starting_balance=default_conf["dry_run_wallet"],
     )
     over = hl.hyperopt_loss_function(
@@ -185,7 +225,10 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
         max_date=datetime(2019, 5, 1),
         config=default_conf,
         processed=None,
-        backtest_stats={"profit_total": results_over["profit_abs"].sum()},
+        backtest_stats={
+            "profit_total": results_over["profit_abs"].sum(),
+            "results_per_pair": pair_results_over,
+        },
         starting_balance=default_conf["dry_run_wallet"],
     )
     under = hl.hyperopt_loss_function(
@@ -195,7 +238,10 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
         max_date=datetime(2019, 5, 1),
         config=default_conf,
         processed=None,
-        backtest_stats={"profit_total": results_under["profit_abs"].sum()},
+        backtest_stats={
+            "profit_total": results_under["profit_abs"].sum(),
+            "results_per_pair": pair_results_under,
+        },
         starting_balance=default_conf["dry_run_wallet"],
     )
     assert over < correct