Short-trades need to be supported by your exchange and market configuration! Short-entries can be created by setting enter_short (corresponds to enter_long for long trades). shift ( 1 )) & # Guard ( dataframe > 0 ) # Make sure Volume is not 0 ), ] = ( 1, 'rsi_cross' ) return dataframe Enter short trades
loc, 30 )) & # Signal: RSI crosses above 30 ( dataframe dataframe. MINUS_DI ( dataframe ) return dataframeĭef populate_entry_trend ( self, dataframe : DataFrame, metadata : dict ) -> DataFrame : """ Based on TA indicators, populates the buy signal for the given dataframe :param dataframe: DataFrame populated with indicators :param metadata: Additional information, like the currently traded pair :return: DataFrame with buy column """ dataframe. HT_SINE ( dataframe ) dataframe = hilbert dataframe = hilbert dataframe = ta. MACD ( dataframe ) dataframe = macd dataframe = macd dataframe = macd hilbert = ta. EMA ( dataframe, timeperiod = 100 ) dataframe = awesome_oscillator ( dataframe ) macd = ta. EMA ( dataframe, timeperiod = 50 ) dataframe = ta. EMA ( dataframe, timeperiod = 10 ) dataframe = ta. EMA ( dataframe, timeperiod = 5 ) dataframe = ta. TEMA ( dataframe, timeperiod = 9 ) dataframe = ta. SMA ( dataframe, timeperiod = 40 ) dataframe = ta. BBANDS ( dataframe, nbdevup = 2, nbdevdn = 2 ) dataframe = ta. STOCHF ( dataframe ) dataframe = stoch dataframe = stoch dataframe = ta. :param dataframe: Dataframe with data from the exchange :param metadata: Additional information, like the currently traded pair :return: a Dataframe with all mandatory indicators for the strategies """ dataframe = ta. Let uncomment only the indicator you are using in your strategies or your hyperopt configuration, otherwise you will waste your memory and CPU usage. The current version is 3 - which is also the default when it's not set explicitly in the strategy.įuture versions will require this to be set.ĭef populate_indicators ( self, dataframe : DataFrame, metadata : dict ) -> DataFrame : """ Adds several different TA indicators to the given DataFrame Performance Note: For the best performance be frugal on the number of indicators you are using. You can test it with the parameter: -strategy SampleStrategyĪdditionally, there is an attribute called INTERFACE_VERSION, which defines the version of the strategy interface the bot should use.
The bot also include a sample strategy called SampleStrategy you can update: user_data/strategies/sample_strategy.py. Anatomy of a strategy ¶Ī strategy file contains all the information needed to build a good strategy: Use -template minimal to get an empty strategy without any indicator examples, or -template advanced to get a template with most callbacks defined. Different template levelsįreqtrade new-strategy has an additional parameter, -template, which controls the amount of pre-build information you get in the created strategy. This is just a template file, which will most likely not be profitable out of the box. Peeking into the future while backtesting Prevent trades from happening for a specific pairĬommon mistakes when developing strategies Informative pairs decorator data (DataProvider)
0 kommentar(er)
