Remove hyperopt-loss default option

Force users to make a concious choice on a hyperopt-loss function

.github/workflows/ci.yml

@@ -88,7 +88,7 @@ jobs:
       run: |
         cp config.json.example config.json
         freqtrade create-userdir --userdir user_data
-        freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --print-all
+        freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
 
     - name: Flake8
       run: |

.travis.yml

@@ -33,7 +33,7 @@ jobs:
     - script:
       - cp config.json.example config.json
       - freqtrade create-userdir --userdir user_data
-      - freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt
+      - freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily
       name: hyperopt
     - script: flake8
       name: flake8

docs/advanced-hyperopt.md

@@ -27,9 +27,9 @@ class MyAwesomeHyperOpt2(MyAwesomeHyperOpt):
 and then quickly switch between hyperopt classes, running optimization process with hyperopt class you need in each particular case:
 
 ```
-$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt --strategy MyAwesomeStrategy ...
+$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --strategy MyAwesomeStrategy ...
 or
-$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt2 --strategy MyAwesomeStrategy ...
+$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt2 --hyperopt-loss SharpeHyperOptLossDaily --strategy MyAwesomeStrategy ...
 ```
 
 ## Creating and using a custom loss function

docs/bot-usage.md

@@ -356,8 +356,7 @@ optional arguments:
                         Hyperopt-loss-functions are: DefaultHyperOptLoss,
                         OnlyProfitHyperOptLoss, SharpeHyperOptLoss,
                         SharpeHyperOptLossDaily, SortinoHyperOptLoss,
-                        SortinoHyperOptLossDaily.(default:
-                        `DefaultHyperOptLoss`).
+                        SortinoHyperOptLossDaily.
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).

docs/faq.md

@@ -140,7 +140,7 @@ Since hyperopt uses Bayesian search, running for too many epochs may not produce
 It's therefore recommended to run between 500-1000 epochs over and over until you hit at least 10.000 epochs in total (or are satisfied with the result). You can best judge by looking at the results - if the bot keeps discovering better strategies, it's best to keep on going.
 
 ```bash
-freqtrade hyperopt --hyperop SampleHyperopt --strategy SampleStrategy -e 1000 
+freqtrade hyperopt --hyperop SampleHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy SampleStrategy -e 1000
 ```
 
 ### Why does it take a long time to run hyperopt?

docs/hyperopt.md

@@ -80,7 +80,7 @@ Rarely you may also need to override:
     # Have a working strategy at hand.
     freqtrade new-hyperopt --hyperopt EmptyHyperopt
 
-    freqtrade hyperopt --hyperopt EmptyHyperopt --spaces roi stoploss trailing --strategy MyWorkingStrategy --config config.json -e 100
+    freqtrade hyperopt --hyperopt EmptyHyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi stoploss trailing --strategy MyWorkingStrategy --config config.json -e 100
     ```
 
 ### 1. Install a Custom Hyperopt File
@@ -205,14 +205,12 @@ add it to the `populate_indicators()` method in your custom hyperopt file.
 
 Each hyperparameter tuning requires a target. This is usually defined as a loss function (sometimes also called objective function), which should decrease for more desirable results, and increase for bad results.
 
-By default, Freqtrade uses a loss function, which has been with freqtrade since the beginning and optimizes mostly for short trade duration and avoiding losses.
-
-A different loss function can be specified by using the `--hyperopt-loss <Class-name>` argument.
+A loss function must be specified via the `--hyperopt-loss <Class-name>` argument (or optionally via the configuration under the `"hyperopt_loss"` key).
 This class should be in its own file within the `user_data/hyperopts/` directory.
 
 Currently, the following loss functions are builtin:
 
-* `DefaultHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function)
+* `DefaultHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function) - Mostly for short trade duration and avoiding losses.
 * `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration)
 * `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on trade returns relative to standard deviation)
 * `SharpeHyperOptLossDaily` (optimizes Sharpe Ratio calculated on **daily** trade returns relative to standard deviation)
@@ -229,7 +227,7 @@ Because hyperopt tries a lot of combinations to find the best parameters it will
 We strongly recommend to use `screen` or `tmux` to prevent any connection loss.
 
 ```bash
-freqtrade hyperopt --config config.json --hyperopt <hyperoptname> --strategy <strategyname> -e 500 --spaces all
+freqtrade hyperopt --config config.json --hyperopt <hyperoptname> --hyperopt-loss <hyperoptlossname> --strategy <strategyname> -e 500 --spaces all
 ```
 
 Use `<hyperoptname>` as the name of the custom hyperopt used.
@@ -263,7 +261,7 @@ freqtrade hyperopt --hyperopt <hyperoptname> --strategy <strategyname> --timeran
 Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided.
 
 ```bash
-freqtrade hyperopt --strategy SampleStrategy --hyperopt SampleHyperopt
+freqtrade hyperopt --hyperopt SampleHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy SampleStrategy
 ```
 
 ### Running Hyperopt with Smaller Search Space

freqtrade/commands/cli_options.py

@@ -258,10 +258,8 @@ AVAILABLE_CLI_OPTIONS = {
         'Different functions can generate completely different results, '
         'since the target for optimization is different. Built-in Hyperopt-loss-functions are: '
         'DefaultHyperOptLoss, OnlyProfitHyperOptLoss, SharpeHyperOptLoss, SharpeHyperOptLossDaily, '
-        'SortinoHyperOptLoss, SortinoHyperOptLossDaily.'
-        '(default: `%(default)s`).',
+        'SortinoHyperOptLoss, SortinoHyperOptLossDaily.',
         metavar='NAME',
-        default=constants.DEFAULT_HYPEROPT_LOSS,
     ),
     "hyperoptexportfilename": Arg(
         '--hyperopt-filename',

freqtrade/constants.py

@@ -11,7 +11,6 @@ DEFAULT_EXCHANGE = 'bittrex'
 PROCESS_THROTTLE_SECS = 5  # sec
 HYPEROPT_EPOCH = 100  # epochs
 RETRY_TIMEOUT = 30  # sec
-DEFAULT_HYPEROPT_LOSS = 'DefaultHyperOptLoss'
 DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite'
 DEFAULT_DB_DRYRUN_URL = 'sqlite:///tradesv3.dryrun.sqlite'
 UNLIMITED_STAKE_AMOUNT = 'unlimited'

freqtrade/resolvers/hyperopt_resolver.py

@@ -7,7 +7,7 @@ import logging
 from pathlib import Path
 from typing import Dict
 
-from freqtrade.constants import DEFAULT_HYPEROPT_LOSS, USERPATH_HYPEROPTS
+from freqtrade.constants import USERPATH_HYPEROPTS
 from freqtrade.exceptions import OperationalException
 from freqtrade.optimize.hyperopt_interface import IHyperOpt
 from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
@@ -70,10 +70,10 @@ class HyperOptLossResolver(IResolver):
         :param config: configuration dictionary
         """
 
-        # Verify the hyperopt_loss is in the configuration, otherwise fallback to the
-        # default hyperopt loss
-        hyperoptloss_name = config.get('hyperopt_loss') or DEFAULT_HYPEROPT_LOSS
-
+        hyperoptloss_name = config.get('hyperopt_loss')
+        if not hyperoptloss_name:
+            raise OperationalException("No Hyperopt loss set. Please use `--hyperopt-loss` to "
+                                       "specify the Hyperopt-Loss class to use.")
         hyperoptloss = HyperOptLossResolver.load_object(hyperoptloss_name,
                                                         config, kwargs={},
                                                         extra_dir=config.get('hyperopt_path'))