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Merge pull request #2123 from freqtrade/hyperoptloss_help

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[minor] Improve hyperopt-loss docs
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Matthias 2019-08-12 14:08:32 +02:00 committed by GitHub
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9
docs/bot-usage.md
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@ -256,12 +256,13 @@ optional arguments:
--continue Continue hyperopt from previous runs. By default,
temporary files will be removed and hyperopt will
start from scratch.
--hyperopt-loss NAME
Specify the class name of the hyperopt loss function
--hyperopt-loss NAME Specify the class name of the hyperopt loss function
class (IHyperOptLoss). Different functions can
generate completely different results, since the
target for optimization is different. (default:
`DefaultHyperOptLoss`).
target for optimization is different. Built-in
Hyperopt-loss-functions are: DefaultHyperOptLoss,
OnlyProfitHyperOptLoss, SharpeHyperOptLoss.
(default: `DefaultHyperOptLoss`).
```
## Edge commands

6
docs/hyperopt.md
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@ -164,7 +164,11 @@ By default, FreqTrade uses a loss function, which has been with freqtrade since
A different loss function can be specified by using the `--hyperopt-loss <Class-name>` argument.
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), `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on the trade returns) and `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration).
Currently, the following loss functions are builtin:
* `DefaultHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function)
* `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration)
* `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on the trade returns)
### Creating and using a custom loss function

4
freqtrade/configuration/cli_options.py
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@ -226,7 +226,9 @@ AVAILABLE_CLI_OPTIONS = {
'--hyperopt-loss',
help='Specify the class name of the hyperopt loss function class (IHyperOptLoss). '
'Different functions can generate completely different results, '
'since the target for optimization is different. (default: `%(default)s`).',
'since the target for optimization is different. Built-in Hyperopt-loss-functions are: '
'DefaultHyperOptLoss, OnlyProfitHyperOptLoss, SharpeHyperOptLoss.'
'(default: `%(default)s`).',
metavar='NAME',
default=constants.DEFAULT_HYPEROPT_LOSS,
),