198 lines
7.7 KiB
Markdown
198 lines
7.7 KiB
Markdown
# Bot usage
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This page explains the difference parameters of the bot and how to run
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it.
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## Table of Contents
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- [Bot commands](#bot-commands)
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- [Backtesting commands](#backtesting-commands)
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- [Hyperopt commands](#hyperopt-commands)
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## Bot commands
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```
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usage: main.py [-h] [-v] [--version] [-c PATH] [-d PATH] [-s NAME]
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[--strategy-path PATH] [--dynamic-whitelist [INT]]
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[--dry-run-db]
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{backtesting,hyperopt} ...
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Simple High Frequency Trading Bot for crypto currencies
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positional arguments:
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{backtesting,hyperopt}
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backtesting backtesting module
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hyperopt hyperopt module
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optional arguments:
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-h, --help show this help message and exit
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-v, --verbose be verbose
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--version show program's version number and exit
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-c PATH, --config PATH
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specify configuration file (default: config.json)
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-d PATH, --datadir PATH
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path to backtest data (default:
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freqtrade/tests/testdata
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-s NAME, --strategy NAME
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specify strategy class name (default: DefaultStrategy)
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--strategy-path PATH specify additional strategy lookup path
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--dynamic-whitelist [INT]
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dynamically generate and update whitelist based on 24h
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BaseVolume (Default 20 currencies)
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--dry-run-db Force dry run to use a local DB
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"tradesv3.dry_run.sqlite" instead of memory DB. Work
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only if dry_run is enabled.
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```
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### How to use a different config file?
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The bot allows you to select which config file you want to use. Per
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default, the bot will load the file `./config.json`
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```bash
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python3 ./freqtrade/main.py -c path/far/far/away/config.json
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```
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### How to use --strategy?
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This parameter will allow you to load your custom strategy class.
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Per default without `--strategy` or `-s` the bot will load the
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`DefaultStrategy` included with the bot (`freqtrade/strategy/default_strategy.py`).
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The bot will search your strategy file within `user_data/strategies` and `freqtrade/strategy`.
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To load a strategy, simply pass the class name (e.g.: `CustomStrategy`) in this parameter.
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**Example:**
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In `user_data/strategies` you have a file `my_awesome_strategy.py` which has
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a strategy class called `AwesomeStrategy` to load it:
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```bash
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python3 ./freqtrade/main.py --strategy AwesomeStrategy
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```
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If the bot does not find your strategy file, it will display in an error
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message the reason (File not found, or errors in your code).
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Learn more about strategy file in [optimize your bot](https://github.com/gcarq/freqtrade/blob/develop/docs/bot-optimization.md).
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### How to use --strategy-path?
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This parameter allows you to add an additional strategy lookup path, which gets
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checked before the default locations (The passed path must be a folder!):
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```bash
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python3 ./freqtrade/main.py --strategy AwesomeStrategy --strategy-path /some/folder
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```
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#### How to install a strategy?
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This is very simple. Copy paste your strategy file into the folder
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`user_data/strategies` or use `--strategy-path`. And voila, the bot is ready to use it.
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### How to use --dynamic-whitelist?
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Per default `--dynamic-whitelist` will retrieve the 20 currencies based
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on BaseVolume. This value can be changed when you run the script.
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**By Default**
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Get the 20 currencies based on BaseVolume.
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```bash
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python3 ./freqtrade/main.py --dynamic-whitelist
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```
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**Customize the number of currencies to retrieve**
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Get the 30 currencies based on BaseVolume.
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```bash
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python3 ./freqtrade/main.py --dynamic-whitelist 30
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```
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**Exception**
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`--dynamic-whitelist` must be greater than 0. If you enter 0 or a
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negative value (e.g -2), `--dynamic-whitelist` will use the default
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value (20).
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### How to use --dry-run-db?
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When you run the bot in Dry-run mode, per default no transactions are
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stored in a database. If you want to store your bot actions in a DB
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using `--dry-run-db`. This command will use a separate database file
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`tradesv3.dry_run.sqlite`
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```bash
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python3 ./freqtrade/main.py -c config.json --dry-run-db
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```
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## Backtesting commands
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Backtesting also uses the config specified via `-c/--config`.
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```
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usage: main.py backtesting [-h] [-i TICKER_INTERVAL] [--realistic-simulation]
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[--timerange TIMERANGE] [-l] [-r] [--export EXPORT]
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[--export-filename EXPORTFILENAME]
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optional arguments:
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-h, --help show this help message and exit
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-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
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specify ticker interval (1m, 5m, 30m, 1h, 1d)
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--realistic-simulation
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uses max_open_trades from config to simulate real
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world limitations
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--timerange TIMERANGE
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specify what timerange of data to use.
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-l, --live using live data
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-r, --refresh-pairs-cached
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refresh the pairs files in tests/testdata with the
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latest data from the exchange. Use it if you want to
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run your backtesting with up-to-date data.
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--export EXPORT export backtest results, argument are: trades Example
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--export=trades
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--export-filename EXPORTFILENAME
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Save backtest results to this filename requires
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--export to be set as well Example --export-
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filename=backtest_today.json (default: backtest-
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result.json
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```
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### How to use --refresh-pairs-cached parameter?
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The first time your run Backtesting, it will take the pairs you have
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set in your config file and download data from Bittrex.
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If for any reason you want to update your data set, you use
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`--refresh-pairs-cached` to force Backtesting to update the data it has.
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**Use it only if you want to update your data set. You will not be able
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to come back to the previous version.**
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To test your strategy with latest data, we recommend continuing using
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the parameter `-l` or `--live`.
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## Hyperopt commands
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It is possible to use hyperopt for trading strategy optimization.
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Hyperopt uses an internal json config return by `hyperopt_optimize_conf()`
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located in `freqtrade/optimize/hyperopt_conf.py`.
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```
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usage: main.py hyperopt [-h] [-i TICKER_INTERVAL] [--realistic-simulation]
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[--timerange TIMERANGE] [-e INT] [--use-mongodb]
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[-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]]
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optional arguments:
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-h, --help show this help message and exit
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-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
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specify ticker interval (1m, 5m, 30m, 1h, 1d)
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--realistic-simulation
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uses max_open_trades from config to simulate real
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world limitations
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--timerange TIMERANGE
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specify what timerange of data to use.
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-e INT, --epochs INT specify number of epochs (default: 100)
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--use-mongodb parallelize evaluations with mongodb (requires mongod
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in PATH)
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-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...], --spaces {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]
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Specify which parameters to hyperopt. Space separate
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list. Default: all
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```
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## A parameter missing in the configuration?
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All parameters for `main.py`, `backtesting`, `hyperopt` are referenced
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in [misc.py](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/misc.py#L84)
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## Next step
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The optimal strategy of the bot will change with time depending of the
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market trends. The next step is to
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[optimize your bot](https://github.com/gcarq/freqtrade/blob/develop/docs/bot-optimization.md).
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