Add sample loss and improve docstring

freqtrade/optimize/default_hyperopt_loss.py

@@ -37,10 +37,11 @@ class DefaultHyperOptLoss(IHyperOptLoss):
                                *args, **kwargs) -> float:
         """
         Objective function, returns smaller number for better results
-        This is the legacy algorithm (used until now in freqtrade).
+        This is the Default algorithm
         Weights are distributed as follows:
         * 0.4 to trade duration
         * 0.25: Avoiding trade loss
+        * 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above
         """
         total_profit = results.profit_percent.sum()
         trade_duration = results.trade_duration.mean()