Start the bot

This page explains the different parameters of the bot and how to run it.

Note

If you've used setup.sh, don't forget to activate your virtual environment (source .env/bin/activate) before running freqtrade commands.

Bot commands

usage: freqtrade [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
                 [--userdir PATH] [-s NAME] [--strategy-path PATH]
                 [--db-url PATH] [--sd-notify]
                 {backtesting,edge,hyperopt,create-userdir,list-exchanges,list-timeframes,download-data,plot-dataframe,plot-profit}
                 ...

Free, open source crypto trading bot

positional arguments:
  {backtesting,edge,hyperopt,create-userdir,list-exchanges,list-timeframes,download-data,plot-dataframe,plot-profit}
    backtesting         Backtesting module.
    edge                Edge module.
    hyperopt            Hyperopt module.
    create-userdir      Create user-data directory.
    list-exchanges      Print available exchanges.
    list-timeframes     Print available ticker intervals (timeframes) for the
                        exchange.
    download-data       Download backtesting data.
    plot-dataframe      Plot candles with indicators.
    plot-profit         Generate plot showing profits.

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
  --logfile FILE        Log to the file specified.
  -V, --version         show program's version number and exit
  -c PATH, --config PATH
                        Specify configuration file (default: `config.json`).
                        Multiple --config options may be used. Can be set to
                        `-` to read config from stdin.
  -d PATH, --datadir PATH
                        Path to directory with historical backtesting data.
  --userdir PATH, --user-data-dir PATH
                        Path to userdata directory.
  -s NAME, --strategy NAME
                        Specify strategy class name (default:
                        `DefaultStrategy`).
  --strategy-path PATH  Specify additional strategy lookup path.
  --db-url PATH         Override trades database URL, this is useful in custom
                        deployments (default: `sqlite:///tradesv3.sqlite` for
                        Live Run mode, `sqlite://` for Dry Run).
  --sd-notify           Notify systemd service manager.

How to specify which configuration file be used?

The bot allows you to select which configuration file you want to use by means of the -c/--config command line option:

freqtrade -c path/far/far/away/config.json

Per default, the bot loads the config.json configuration file from the current working directory.

How to use multiple configuration files?

The bot allows you to use multiple configuration files by specifying multiple -c/--config options in the command line. Configuration parameters defined in the latter configuration files override parameters with the same name defined in the previous configuration files specified in the command line earlier.

For example, you can make a separate configuration file with your key and secrete for the Exchange you use for trading, specify default configuration file with empty key and secrete values while running in the Dry Mode (which does not actually require them):

freqtrade -c ./config.json

and specify both configuration files when running in the normal Live Trade Mode:

freqtrade -c ./config.json -c path/to/secrets/keys.config.json

This could help you hide your private Exchange key and Exchange secrete on you local machine by setting appropriate file permissions for the file which contains actual secrets and, additionally, prevent unintended disclosure of sensitive private data when you publish examples of your configuration in the project issues or in the Internet.

See more details on this technique with examples in the documentation page on configuration.

Where to store custom data

Freqtrade allows the creation of a user-data directory using freqtrade create-userdir --userdir someDirectory. This directory will look as follows:

user_data/
├── backtest_results
├── data
├── hyperopts
├── hyperopt_results
├── plot
└── strategies

You can add the entry "user_data_dir" setting to your configuration, to always point your bot to this directory. Alternatively, pass in --userdir to every command. The bot will fail to start if the directory does not exist, but will create necessary subdirectories.

This directory should contain your custom strategies, custom hyperopts and hyperopt loss functions, backtesting historical data (downloaded using either backtesting command or the download script) and plot outputs.

It is recommended to use version control to keep track of changes to your strategies.

How to use --strategy?

This parameter will allow you to load your custom strategy class. Per default without --strategy or -s the bot will load the DefaultStrategy included with the bot (freqtrade/strategy/default_strategy.py).

The bot will search your strategy file within user_data/strategies and freqtrade/strategy.

To load a strategy, simply pass the class name (e.g.: CustomStrategy) in this parameter.

Example: In user_data/strategies you have a file my_awesome_strategy.py which has a strategy class called AwesomeStrategy to load it:

freqtrade --strategy AwesomeStrategy

If the bot does not find your strategy file, it will display in an error message the reason (File not found, or errors in your code).

Learn more about strategy file in Strategy Customization.

How to use --strategy-path?

This parameter allows you to add an additional strategy lookup path, which gets checked before the default locations (The passed path must be a directory!):

freqtrade --strategy AwesomeStrategy --strategy-path /some/directory

How to install a strategy?

This is very simple. Copy paste your strategy file into the directory user_data/strategies or use --strategy-path. And voila, the bot is ready to use it.

How to use --db-url?

When you run the bot in Dry-run mode, per default no transactions are stored in a database. If you want to store your bot actions in a DB using --db-url. This can also be used to specify a custom database in production mode. Example command:

freqtrade -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite

Backtesting commands

Backtesting also uses the config specified via -c/--config.

usage: freqtrade backtesting [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
                             [--max_open_trades INT]
                             [--stake_amount STAKE_AMOUNT] [--fee FLOAT]
                             [--eps] [--dmmp]
                             [--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
                             [--export EXPORT] [--export-filename PATH]

optional arguments:
  -h, --help            show this help message and exit
  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
                        Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                        `1d`).
  --timerange TIMERANGE
                        Specify what timerange of data to use.
  --max_open_trades INT
                        Specify max_open_trades to use.
  --stake_amount STAKE_AMOUNT
                        Specify stake_amount.
  --fee FLOAT           Specify fee ratio. Will be applied twice (on trade
                        entry and exit).
  --eps, --enable-position-stacking
                        Allow buying the same pair multiple times (position
                        stacking).
  --dmmp, --disable-max-market-positions
                        Disable applying `max_open_trades` during backtest
                        (same as setting `max_open_trades` to a very high
                        number).
  --strategy-list STRATEGY_LIST [STRATEGY_LIST ...]
                        Provide a space-separated list of strategies to
                        backtest. Please note that ticker-interval needs to be
                        set either in config or via command line. When using
                        this together with `--export trades`, the strategy-
                        name is injected into the filename (so `backtest-
                        data.json` becomes `backtest-data-
                        DefaultStrategy.json`
  --export EXPORT       Export backtest results, argument are: trades.
                        Example: `--export=trades`
  --export-filename PATH
                        Save backtest results to the file with this filename
                        (default: `user_data/backtest_results/backtest-
                        result.json`). Requires `--export` to be set as well.
                        Example: `--export-filename=user_data/backtest_results
                        /backtest_today.json`

Getting historic data for backtesting

The first time your run Backtesting, you will need to download some historic data first. This can be accomplished by using freqtrade download-data.
Check the corresponding help page section for more details

Hyperopt commands

To optimize your strategy, you can use hyperopt parameter hyperoptimization to find optimal parameter values for your stategy.

usage: freqtrade hyperopt [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
                          [--max_open_trades INT]
                          [--stake_amount STAKE_AMOUNT] [--fee FLOAT]
                          [--customhyperopt NAME] [--hyperopt-path PATH]
                          [--eps] [-e INT]
                          [-s {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...]]
                          [--dmmp] [--print-all] [--no-color] [--print-json]
                          [-j JOBS] [--random-state INT] [--min-trades INT]
                          [--continue] [--hyperopt-loss NAME]

optional arguments:
  -h, --help            show this help message and exit
  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
                        Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                        `1d`).
  --timerange TIMERANGE
                        Specify what timerange of data to use.
  --max_open_trades INT
                        Specify max_open_trades to use.
  --stake_amount STAKE_AMOUNT
                        Specify stake_amount.
  --fee FLOAT           Specify fee ratio. Will be applied twice (on trade
                        entry and exit).
  --customhyperopt NAME
                        Specify hyperopt class name (default:
                        `DefaultHyperOpt`).
  --hyperopt-path PATH  Specify additional lookup path for Hyperopts and
                        Hyperopt Loss functions.
  --eps, --enable-position-stacking
                        Allow buying the same pair multiple times (position
                        stacking).
  -e INT, --epochs INT  Specify number of epochs (default: 100).
  -s {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...], --spaces {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...]
                        Specify which parameters to hyperopt. Space-separated
                        list. Default: `all`.
  --dmmp, --disable-max-market-positions
                        Disable applying `max_open_trades` during backtest
                        (same as setting `max_open_trades` to a very high
                        number).
  --print-all           Print all results, not only the best ones.
  --no-color            Disable colorization of hyperopt results. May be
                        useful if you are redirecting output to a file.
  --print-json          Print best result detailization in JSON format.
  -j JOBS, --job-workers JOBS
                        The number of concurrently running jobs for
                        hyperoptimization (hyperopt worker processes). If -1
                        (default), all CPUs are used, for -2, all CPUs but one
                        are used, etc. If 1 is given, no parallel computing
                        code is used at all.
  --random-state INT    Set random state to some positive integer for
                        reproducible hyperopt results.
  --min-trades INT      Set minimal desired number of trades for evaluations
                        in the hyperopt optimization path (default: 1).
  --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
                        class (IHyperOptLoss). Different functions can
                        generate completely different results, since the
                        target for optimization is different. Built-in
                        Hyperopt-loss-functions are: DefaultHyperOptLoss,
                        OnlyProfitHyperOptLoss, SharpeHyperOptLoss.(default:
                        `DefaultHyperOptLoss`).

Edge commands

To know your trade expectancy and winrate against historical data, you can use Edge.

usage: freqtrade edge [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
                      [--max_open_trades INT] [--stake_amount STAKE_AMOUNT]
                      [--fee FLOAT] [--stoplosses STOPLOSS_RANGE]

optional arguments:
  -h, --help            show this help message and exit
  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
                        Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                        `1d`).
  --timerange TIMERANGE
                        Specify what timerange of data to use.
  --max_open_trades INT
                        Specify max_open_trades to use.
  --stake_amount STAKE_AMOUNT
                        Specify stake_amount.
  --fee FLOAT           Specify fee ratio. Will be applied twice (on trade
                        entry and exit).
  --stoplosses STOPLOSS_RANGE
                        Defines a range of stoploss values against which edge
                        will assess the strategy. The format is "min,max,step"
                        (without any space). Example:
                        `--stoplosses=-0.01,-0.1,-0.001`

To understand edge and how to read the results, please read the edge documentation.

Next step

The optimal strategy of the bot will change with time depending of the market trends. The next step is to Strategy Customization.