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Freqtrade
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Plotting
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Initializing search
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GitHub
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Freqtrade
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GitHub
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Home
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Quickstart with Docker
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Installation
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Installation
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Linux/MacOS/Raspberry
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Windows
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Freqtrade Basics
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Configuration
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Strategy Quickstart
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Strategy Customization
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Strategy Callbacks
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Stoploss
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Plugins
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Start the bot
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Control the bot
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< span class = "md-nav__icon md-icon" > < / span >
Control the bot
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< a href = "../telegram-usage/" class = "md-nav__link" >
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Telegram
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< / a >
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< a href = "../freq-ui/" class = "md-nav__link" >
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freqUI
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REST API
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Web Hook
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< a href = "../data-download/" class = "md-nav__link" >
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Data Downloading
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Backtesting
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Hyperopt
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FreqAI
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< h1 id = "plotting" > Plotting< a class = "headerlink" href = "#plotting" title = "Permanent link" > ¶ < / a > < / h1 >
< p > This page explains how to plot prices, indicators and profits.< / p >
< div class = "admonition warning" >
< p class = "admonition-title" > Deprecated< / p >
< p > The commands described in this page (< code > plot-dataframe< / code > , < code > plot-profit< / code > ) should be considered deprecated and are in maintenance mode.
This is mostly for the performance problems even medium sized plots can cause, but also because "store a file and open it in a browser" isn't very intuitive from a UI perspective.< / p >
< p > While there are no immediate plans to remove them, they are not actively maintained - and may be removed short-term should major changes be required to keep them working.< / p >
< p > Please use < a href = "../freq-ui/" > FreqUI< / a > for plotting needs, which doesn't struggle with the same performance problems.< / p >
< / div >
< h2 id = "installation-setup" > Installation / Setup< a class = "headerlink" href = "#installation-setup" title = "Permanent link" > ¶ < / a > < / h2 >
< p > Plotting modules use the Plotly library. You can install / upgrade this by running the following command:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > pip< span class = "w" > < / span > install< span class = "w" > < / span > -U< span class = "w" > < / span > -r< span class = "w" > < / span > requirements-plot.txt
< / code > < / pre > < / div >
< h2 id = "plot-price-and-indicators" > Plot price and indicators< a class = "headerlink" href = "#plot-price-and-indicators" title = "Permanent link" > ¶ < / a > < / h2 >
< p > The < code > freqtrade plot-dataframe< / code > subcommand shows an interactive graph with three subplots:< / p >
< ul >
< li > Main plot with candlesticks and indicators following price (sma/ema)< / li >
< li > Volume bars< / li >
< li > Additional indicators as specified by < code > --indicators2< / code > < / li >
< / ul >
< p > < img alt = "plot-dataframe" src = "../assets/plot-dataframe.png" / > < / p >
< p > Possible arguments:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH] [-s NAME]
[--strategy-path PATH] [-p PAIRS [PAIRS ...]]
[--indicators1 INDICATORS1 [INDICATORS1 ...]]
[--indicators2 INDICATORS2 [INDICATORS2 ...]]
[--plot-limit INT] [--db-url PATH]
[--trade-source {DB,file}] [--export EXPORT]
[--export-filename PATH]
[--timerange TIMERANGE] [-i TIMEFRAME]
[--no-trades]
optional arguments:
-h, --help show this help message and exit
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
--indicators1 INDICATORS1 [INDICATORS1 ...]
Set indicators from your strategy you want in the
first row of the graph. Space-separated list. Example:
`ema3 ema5`. Default: `[' sma' , ' ema3' , ' ema5' ]`.
--indicators2 INDICATORS2 [INDICATORS2 ...]
Set indicators from your strategy you want in the
third row of the graph. Space-separated list. Example:
`fastd fastk`. Default: `[' macd' , ' macdsignal' ]`.
--plot-limit INT Specify tick limit for plotting. Notice: too high
values cause huge files. Default: 750.
--db-url PATH Override trades database URL, this is useful in custom
deployments (default: `sqlite:///tradesv3.sqlite` for
Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
Dry Run).
--trade-source {DB,file}
Specify the source for trades (Can be DB or file
(backtest file)) Default: file
--export EXPORT Export backtest results, argument are: trades.
Example: `--export=trades`
--export-filename PATH
Save backtest results to the file with this filename.
Requires `--export` to be set as well. Example:
`--export-filename=user_data/backtest_results/backtest
_today.json`
--timerange TIMERANGE
Specify what timerange of data to use.
-i TIMEFRAME, --timeframe TIMEFRAME
Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
--no-trades Skip using trades from backtesting file and DB.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE Log to the file specified. Special values are:
' syslog' , ' journald' . See the documentation for more
details.
-V, --version show program' s version number and exit
-c PATH, --config PATH
Specify configuration file (default:
`userdir/config.json` or `config.json` whichever
exists). 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.
Strategy arguments:
-s NAME, --strategy NAME
Specify strategy class name which will be used by the
bot.
--strategy-path PATH Specify additional strategy lookup path.
< / code > < / pre > < / div >
< p > Example:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-dataframe< span class = "w" > < / span > -p< span class = "w" > < / span > BTC/ETH< span class = "w" > < / span > --strategy< span class = "w" > < / span > AwesomeStrategy
< / code > < / pre > < / div >
< p > The < code > -p/--pairs< / code > argument can be used to specify pairs you would like to plot.< / p >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > The < code > freqtrade plot-dataframe< / code > subcommand generates one plot-file per pair.< / p >
< / div >
< p > Specify custom indicators.
Use < code > --indicators1< / code > for the main plot and < code > --indicators2< / code > for the subplot below (if values are in a different range than prices).< / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-dataframe< span class = "w" > < / span > --strategy< span class = "w" > < / span > AwesomeStrategy< span class = "w" > < / span > -p< span class = "w" > < / span > BTC/ETH< span class = "w" > < / span > --indicators1< span class = "w" > < / span > sma< span class = "w" > < / span > ema< span class = "w" > < / span > --indicators2< span class = "w" > < / span > macd
< / code > < / pre > < / div >
< h3 id = "further-usage-examples" > Further usage examples< a class = "headerlink" href = "#further-usage-examples" title = "Permanent link" > ¶ < / a > < / h3 >
< p > To plot multiple pairs, separate them with a space:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-dataframe< span class = "w" > < / span > --strategy< span class = "w" > < / span > AwesomeStrategy< span class = "w" > < / span > -p< span class = "w" > < / span > BTC/ETH< span class = "w" > < / span > XRP/ETH
< / code > < / pre > < / div >
< p > To plot a timerange (to zoom in)< / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-dataframe< span class = "w" > < / span > --strategy< span class = "w" > < / span > AwesomeStrategy< span class = "w" > < / span > -p< span class = "w" > < / span > BTC/ETH< span class = "w" > < / span > --timerange< span class = "o" > =< / span > < span class = "m" > 20180801< / span > -20180805
< / code > < / pre > < / div >
< p > To plot trades stored in a database use < code > --db-url< / code > in combination with < code > --trade-source DB< / code > :< / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-dataframe< span class = "w" > < / span > --strategy< span class = "w" > < / span > AwesomeStrategy< span class = "w" > < / span > --db-url< span class = "w" > < / span > sqlite:///tradesv3.dry_run.sqlite< span class = "w" > < / span > -p< span class = "w" > < / span > BTC/ETH< span class = "w" > < / span > --trade-source< span class = "w" > < / span > DB
< / code > < / pre > < / div >
< p > To plot trades from a backtesting result, use < code > --export-filename < filename> < / code > < / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-dataframe< span class = "w" > < / span > --strategy< span class = "w" > < / span > AwesomeStrategy< span class = "w" > < / span > --export-filename< span class = "w" > < / span > user_data/backtest_results/backtest-result.json< span class = "w" > < / span > -p< span class = "w" > < / span > BTC/ETH
< / code > < / pre > < / div >
< h3 id = "plot-dataframe-basics" > Plot dataframe basics< a class = "headerlink" href = "#plot-dataframe-basics" title = "Permanent link" > ¶ < / a > < / h3 >
< p > < img alt = "plot-dataframe2" src = "../assets/plot-dataframe2.png" / > < / p >
< p > The < code > plot-dataframe< / code > subcommand requires backtesting data, a strategy and either a backtesting-results file or a database, containing trades corresponding to the strategy.< / p >
< p > The resulting plot will have the following elements:< / p >
< ul >
< li > Green triangles: Buy signals from the strategy. (Note: not every buy signal generates a trade, compare to cyan circles.)< / li >
< li > Red triangles: Sell signals from the strategy. (Also, not every sell signal terminates a trade, compare to red and green squares.)< / li >
< li > Cyan circles: Trade entry points.< / li >
< li > Red squares: Trade exit points for trades with loss or 0% profit.< / li >
< li > Green squares: Trade exit points for profitable trades.< / li >
< li > Indicators with values corresponding to the candle scale (e.g. SMA/EMA), as specified with < code > --indicators1< / code > .< / li >
< li > Volume (bar chart at the bottom of the main chart).< / li >
< li > Indicators with values in different scales (e.g. MACD, RSI) below the volume bars, as specified with < code > --indicators2< / code > .< / li >
< / ul >
< div class = "admonition note" >
< p class = "admonition-title" > Bollinger Bands< / p >
< p > Bollinger bands are automatically added to the plot if the columns < code > bb_lowerband< / code > and < code > bb_upperband< / code > exist, and are painted as a light blue area spanning from the lower band to the upper band.< / p >
< / div >
< h4 id = "advanced-plot-configuration" > Advanced plot configuration< a class = "headerlink" href = "#advanced-plot-configuration" title = "Permanent link" > ¶ < / a > < / h4 >
< p > An advanced plot configuration can be specified in the strategy in the < code > plot_config< / code > parameter.< / p >
< p > Additional features when using < code > plot_config< / code > include:< / p >
< ul >
< li > Specify colors per indicator< / li >
< li > Specify additional subplots< / li >
< li > Specify indicator pairs to fill area in between< / li >
< / ul >
< p > The sample plot configuration below specifies fixed colors for the indicators. Otherwise, consecutive plots may produce different color schemes each time, making comparisons difficult.
It also allows multiple subplots to display both MACD and RSI at the same time.< / p >
< p > Plot type can be configured using < code > type< / code > key. Possible types are:< / p >
< ul >
< li > < code > scatter< / code > corresponding to < code > plotly.graph_objects.Scatter< / code > class (default).< / li >
< li > < code > bar< / code > corresponding to < code > plotly.graph_objects.Bar< / code > class.< / li >
< / ul >
< p > Extra parameters to < code > plotly.graph_objects.*< / code > constructor can be specified in < code > plotly< / code > dict.< / p >
< p > Sample configuration with inline comments explaining the process:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "nd" > @property< / span >
< span class = "k" > def< / span > < span class = "nf" > plot_config< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ):< / span >
< span class = "w" > < / span > < span class = "sd" > " " " < / span >
< span class = "sd" > There are a lot of solutions how to build the return dictionary.< / span >
< span class = "sd" > The only important point is the return value.< / span >
< span class = "sd" > Example:< / span >
< span class = "sd" > plot_config = {' main_plot' : {}, ' subplots' : {}}< / span >
< span class = "sd" > " " " < / span >
< span class = "n" > plot_config< / span > < span class = "o" > =< / span > < span class = "p" > {}< / span >
< span class = "n" > plot_config< / span > < span class = "p" > [< / span > < span class = "s1" > ' main_plot' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "p" > {< / span >
< span class = "c1" > # Configuration for main plot indicators.< / span >
< span class = "c1" > # Assumes 2 parameters, emashort and emalong to be specified.< / span >
< span class = "sa" > f< / span > < span class = "s1" > ' ema_< / span > < span class = "si" > {< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > emashort< / span > < span class = "o" > .< / span > < span class = "n" > value< / span > < span class = "si" > }< / span > < span class = "s1" > ' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' red' < / span > < span class = "p" > },< / span >
< span class = "sa" > f< / span > < span class = "s1" > ' ema_< / span > < span class = "si" > {< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > emalong< / span > < span class = "o" > .< / span > < span class = "n" > value< / span > < span class = "si" > }< / span > < span class = "s1" > ' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' #CCCCCC' < / span > < span class = "p" > },< / span >
< span class = "c1" > # By omitting color, a random color is selected.< / span >
< span class = "s1" > ' sar' < / span > < span class = "p" > :< / span > < span class = "p" > {},< / span >
< span class = "c1" > # fill area between senkou_a and senkou_b< / span >
< span class = "s1" > ' senkou_a' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' green' < / span > < span class = "p" > ,< / span > < span class = "c1" > #optional< / span >
< span class = "s1" > ' fill_to' < / span > < span class = "p" > :< / span > < span class = "s1" > ' senkou_b' < / span > < span class = "p" > ,< / span >
< span class = "s1" > ' fill_label' < / span > < span class = "p" > :< / span > < span class = "s1" > ' Ichimoku Cloud' < / span > < span class = "p" > ,< / span > < span class = "c1" > #optional< / span >
< span class = "s1" > ' fill_color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' rgba(255,76,46,0.2)' < / span > < span class = "p" > ,< / span > < span class = "c1" > #optional< / span >
< span class = "p" > },< / span >
< span class = "c1" > # plot senkou_b, too. Not only the area to it.< / span >
< span class = "s1" > ' senkou_b' < / span > < span class = "p" > :< / span > < span class = "p" > {}< / span >
< span class = "p" > }< / span >
< span class = "n" > plot_config< / span > < span class = "p" > [< / span > < span class = "s1" > ' subplots' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "p" > {< / span >
< span class = "c1" > # Create subplot MACD< / span >
< span class = "s2" > " MACD" < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "s1" > ' macd' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' blue' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' fill_to' < / span > < span class = "p" > :< / span > < span class = "s1" > ' macdhist' < / span > < span class = "p" > },< / span >
< span class = "s1" > ' macdsignal' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' orange' < / span > < span class = "p" > },< / span >
< span class = "s1" > ' macdhist' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' type' < / span > < span class = "p" > :< / span > < span class = "s1" > ' bar' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' plotly' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' opacity' < / span > < span class = "p" > :< / span > < span class = "mf" > 0.9< / span > < span class = "p" > }}< / span >
< span class = "p" > },< / span >
< span class = "c1" > # Additional subplot RSI< / span >
< span class = "s2" > " RSI" < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "s1" > ' rsi' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' red' < / span > < span class = "p" > }< / span >
< span class = "p" > }< / span >
< span class = "p" > }< / span >
< span class = "k" > return< / span > < span class = "n" > plot_config< / span >
< / code > < / pre > < / div >
< details class = "note" >
< summary > As attribute (former method)< / summary >
< p > Assigning plot_config is also possible as Attribute (this used to be the default way).
This has the disadvantage that strategy parameters are not available, preventing certain configurations from working.< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "n" > plot_config< / span > < span class = "o" > =< / span > < span class = "p" > {< / span >
< span class = "s1" > ' main_plot' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "c1" > # Configuration for main plot indicators.< / span >
< span class = "c1" > # Specifies `ema10` to be red, and `ema50` to be a shade of gray< / span >
< span class = "s1" > ' ema10' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' red' < / span > < span class = "p" > },< / span >
< span class = "s1" > ' ema50' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' #CCCCCC' < / span > < span class = "p" > },< / span >
< span class = "c1" > # By omitting color, a random color is selected.< / span >
< span class = "s1" > ' sar' < / span > < span class = "p" > :< / span > < span class = "p" > {},< / span >
< span class = "c1" > # fill area between senkou_a and senkou_b< / span >
< span class = "s1" > ' senkou_a' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' green' < / span > < span class = "p" > ,< / span > < span class = "c1" > #optional< / span >
< span class = "s1" > ' fill_to' < / span > < span class = "p" > :< / span > < span class = "s1" > ' senkou_b' < / span > < span class = "p" > ,< / span >
< span class = "s1" > ' fill_label' < / span > < span class = "p" > :< / span > < span class = "s1" > ' Ichimoku Cloud' < / span > < span class = "p" > ,< / span > < span class = "c1" > #optional< / span >
< span class = "s1" > ' fill_color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' rgba(255,76,46,0.2)' < / span > < span class = "p" > ,< / span > < span class = "c1" > #optional< / span >
< span class = "p" > },< / span >
< span class = "c1" > # plot senkou_b, too. Not only the area to it.< / span >
< span class = "s1" > ' senkou_b' < / span > < span class = "p" > :< / span > < span class = "p" > {}< / span >
< span class = "p" > },< / span >
< span class = "s1" > ' subplots' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "c1" > # Create subplot MACD< / span >
< span class = "s2" > " MACD" < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "s1" > ' macd' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' blue' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' fill_to' < / span > < span class = "p" > :< / span > < span class = "s1" > ' macdhist' < / span > < span class = "p" > },< / span >
< span class = "s1" > ' macdsignal' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' orange' < / span > < span class = "p" > },< / span >
< span class = "s1" > ' macdhist' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' type' < / span > < span class = "p" > :< / span > < span class = "s1" > ' bar' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' plotly' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' opacity' < / span > < span class = "p" > :< / span > < span class = "mf" > 0.9< / span > < span class = "p" > }}< / span >
< span class = "p" > },< / span >
< span class = "c1" > # Additional subplot RSI< / span >
< span class = "s2" > " RSI" < / span > < span class = "p" > :< / span > < span class = "p" > {< / span >
< span class = "s1" > ' rsi' < / span > < span class = "p" > :< / span > < span class = "p" > {< / span > < span class = "s1" > ' color' < / span > < span class = "p" > :< / span > < span class = "s1" > ' red' < / span > < span class = "p" > }< / span >
< span class = "p" > }< / span >
< span class = "p" > }< / span >
< span class = "p" > }< / span >
< / code > < / pre > < / div >
< / details >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > The above configuration assumes that < code > ema10< / code > , < code > ema50< / code > , < code > senkou_a< / code > , < code > senkou_b< / code > ,
< code > macd< / code > , < code > macdsignal< / code > , < code > macdhist< / code > and < code > rsi< / code > are columns in the DataFrame created by the strategy.< / p >
< / div >
< div class = "admonition warning" >
< p class = "admonition-title" > Warning< / p >
< p > < code > plotly< / code > arguments are only supported with plotly library and will not work with freq-ui.< / p >
< / div >
< div class = "admonition note" >
< p class = "admonition-title" > Trade position adjustments< / p >
< p > If < code > position_adjustment_enable< / code > / < code > adjust_trade_position()< / code > is used, the trade initial buy price is averaged over multiple orders and the trade start price will most likely appear outside the candle range.< / p >
< / div >
< h2 id = "plot-profit" > Plot profit< a class = "headerlink" href = "#plot-profit" title = "Permanent link" > ¶ < / a > < / h2 >
< p > < img alt = "plot-profit" src = "../assets/plot-profit.png" / > < / p >
< p > The < code > plot-profit< / code > subcommand shows an interactive graph with three plots:< / p >
< ul >
< li > Average closing price for all pairs.< / li >
< li > The summarized profit made by backtesting.
Note that this is not the real-world profit, but more of an estimate.< / li >
< li > Profit for each individual pair.< / li >
< li > Parallelism of trades.< / li >
< li > Underwater (Periods of drawdown).< / li >
< / ul >
< p > The first graph is good to get a grip of how the overall market progresses.< / p >
< p > The second graph will show if your algorithm works or doesn't.
Perhaps you want an algorithm that steadily makes small profits, or one that acts less often, but makes big swings.
This graph will also highlight the start (and end) of the Max drawdown period.< / p >
< p > The third graph can be useful to spot outliers, events in pairs that cause profit spikes.< / p >
< p > The forth graph can help you analyze trade parallelism, showing how often max_open_trades have been maxed out.< / p >
< p > Possible options for the < code > freqtrade plot-profit< / code > subcommand:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > usage: freqtrade plot-profit [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH] [-s NAME]
[--strategy-path PATH] [-p PAIRS [PAIRS ...]]
[--timerange TIMERANGE] [--export EXPORT]
[--export-filename PATH] [--db-url PATH]
[--trade-source {DB,file}] [-i TIMEFRAME]
optional arguments:
-h, --help show this help message and exit
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
--timerange TIMERANGE
Specify what timerange of data to use.
--export EXPORT Export backtest results, argument are: trades.
Example: `--export=trades`
--export-filename PATH, --backtest-filename PATH
Use backtest results from this filename.
Requires `--export` to be set as well. Example:
`--export-filename=user_data/backtest_results/backtest
_today.json`
--db-url PATH Override trades database URL, this is useful in custom
deployments (default: `sqlite:///tradesv3.sqlite` for
Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
Dry Run).
--trade-source {DB,file}
Specify the source for trades (Can be DB or file
(backtest file)) Default: file
-i TIMEFRAME, --timeframe TIMEFRAME
Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
--auto-open Automatically open generated plot.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE Log to the file specified. Special values are:
' syslog' , ' journald' . See the documentation for more
details.
-V, --version show program' s version number and exit
-c PATH, --config PATH
Specify configuration file (default:
`userdir/config.json` or `config.json` whichever
exists). 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.
Strategy arguments:
-s NAME, --strategy NAME
Specify strategy class name which will be used by the
bot.
--strategy-path PATH Specify additional strategy lookup path.
< / code > < / pre > < / div >
< p > The < code > -p/--pairs< / code > argument, can be used to limit the pairs that are considered for this calculation.< / p >
< p > Examples:< / p >
< p > Use custom backtest-export file< / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-profit< span class = "w" > < / span > -p< span class = "w" > < / span > LTC/BTC< span class = "w" > < / span > --export-filename< span class = "w" > < / span > user_data/backtest_results/backtest-result.json
< / code > < / pre > < / div >
< p > Use custom database< / p >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > plot-profit< span class = "w" > < / span > -p< span class = "w" > < / span > LTC/BTC< span class = "w" > < / span > --db-url< span class = "w" > < / span > sqlite:///tradesv3.sqlite< span class = "w" > < / span > --trade-source< span class = "w" > < / span > DB
< / code > < / pre > < / div >
< div class = "highlight" > < pre > < span > < / span > < code > freqtrade< span class = "w" > < / span > --datadir< span class = "w" > < / span > user_data/data/binance_save/< span class = "w" > < / span > plot-profit< span class = "w" > < / span > -p< span class = "w" > < / span > LTC/BTC
< / code > < / pre > < / div >
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