The DefaultStrategy class is a trading strategy that uses various technical indicators to make buy and sell decisions. Here's a breakdown of what the strategy does:
populate_indicators: This method takes a DataFrame containing raw data from the exchange and adds several technical indicators to it. The indicators include ADX (Average Directional Index), AO (Awesome Oscillator), MACD (Moving Average Convergence Divergence), MFI (Money Flow Index), and others.
Each indicator is calculated and added as a new column in the DataFrame.
populate_buy_trend: This method populates the buy signal for the given DataFrame based on the calculated indicators.
The buy conditions include criteria such as RSI (Relative Strength Index) being below 35, fastd (fast %D) being below 35, ADX being above 30, and plus_di (Plus Directional Indicator) being above 0.5. If any of these conditions are met, the 'buy' column for the corresponding row is set to 1. populate_sell_trend: This method populates the sell signal for the given DataFrame based on the calculated indicators. The sell conditions include criteria such as RSI or fastd crossing above 70, ADX being above 10, and minus_di (Minus Directional Indicator) being above 0. If any of these conditions are met, the strategy considers it a sell signal. Overall, the DefaultStrategy class calculates a set of technical indicators and uses them to determine buy and sell signals for trading. It can be customized by enabling or disabling specific indicators based on the desired trading strategy.
Each indicator is calculated and added as a new column in the DataFrame.
populate_buy_trend: This method populates the buy signal for the given DataFrame based on the calculated indicators.
The buy conditions include criteria such as RSI (Relative Strength Index) being below 35, fastd (fast %D) being below 35, ADX being above 30, and plus_di (Plus Directional Indicator) being above 0.5. If any of these conditions are met, the 'buy' column for the corresponding row is set to 1. populate_sell_trend: This method populates the sell signal for the given DataFrame based on the calculated indicators. The sell conditions include criteria such as RSI or fastd crossing above 70, ADX being above 10, and minus_di (Minus Directional Indicator) being above 0. If any of these conditions are met, the strategy considers it a sell signal. Overall, the DefaultStrategy class calculates a set of technical indicators and uses them to determine buy and sell signals for trading. It can be customized by enabling or disabling specific indicators based on the desired trading strategy.
Traceback (most recent call last): File "/freqtrade/freqtrade/main.py", line 42, in main return_code = args['func'](args) ^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/commands/optimize_commands.py", line 58, in start_backtesting backtesting.start() File "/freqtrade/freqtrade/optimize/backtesting.py", line 1401, in start min_date, max_date = self.backtest_one_strategy(strat, data, timerange) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1318, in backtest_one_strategy preprocessed = self.strategy.advise_all_indicators(data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in advise_all_indicators return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, inreturn {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1410, in advise_indicators return self.populate_indicators(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/default_strategy.py", line 94, in populate_indicators dataframe['blower'] = ta.BBANDS(dataframe, nbdevup=2, nbdevdn=2)['lowerband'] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "talib/_abstract.pxi", line 444, in talib._ta_lib.Function.__call__ File "talib/_abstract.pxi", line 294, in talib._ta_lib.Function.set_function_args File "talib/_abstract.pxi", line 513, in talib._ta_lib.Function.__check_opt_input_value TypeError: Invalid parameter value for nbdevup (expected float, got int)
stoploss: -0.1 timeframe: 5m hash(sha256): bd32929b99b7e89ac0ca3f163d4cd790d883f995032c08000010ef9bbb2c3234 indicators: lowerband upper htsine minus_dm tema plus_dm CDLDRAGONFLYDOJI CDLHANGINGMAN CDLSHOOTINGSTAR CDLGRAVESTONEDOJI close ha_low CDLSPINNINGTOP mfi bb_lowerband ema5 CDLENGULFING fastd_rsi CDL3WHITESOLDIERS fastk macdhist CDLHAMMER htleadsine sma slowd leadsine CDLMORNINGSTAR CDLEVENINGDOJISTAR blower open plus_di fastd ema10 CDLPIERCING CDLEVENINGSTAR sar ha_open CDL3OUTSIDE high macdsignal slowk mid fisher_rsi fastk_rsi ema100 fisher_rsi_norma cci ha_close macd CDL3INSIDE ema3 CDLINVERTEDHAMMER CDLH
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last change: 2024-04-28 08:47:09