The DefaultStrategy class is a trading strategy that utilizes various technical analysis (TA) indicators to make buy and sell decisions. The strategy has three main functions: populate_indicators, populate_buy_trend, and populate_sell_trend. The populate_indicators function takes a raw data DataFrame from the exchange and adds several TA indicators to it.
These indicators include ADX (Average Directional Index), AO (Awesome Oscillator), MACD (Moving Average Convergence Divergence), MFI (Money Flow Index), and others.
Some indicators are commented out, indicating that they are optional and can be uncommented if needed.
The function returns the DataFrame with all the mandatory indicators. The populate_buy_trend function populates the buy signal for the DataFrame based on the TA indicators. In this strategy, a buy signal is generated when the RSI (Relative Strength Index) is below 35, the fast %D (Stochastic Oscillator) is below 35, the ADX is above 30, and the plus DI (Directional Indicator) is above 0.5. Alternatively, a buy signal is also generated when the ADX is above 65 and the plus DI is above 0.5. The function modifies the DataFrame by adding a 'buy' column with a value of 1 for the corresponding buy signals. The populate_sell_trend function populates the sell signal for the DataFrame based on the TA indicators. In this strategy, a sell signal is generated when either the RSI or the fast %D crosses above 70, the ADX is above 10, and the minus DI is greater than 0. Alternatively, a sell signal is also generated when the ADX is above 70 and the minus DI is above 0.5. The function modifies the DataFrame by adding a 'sell' column with a value of 1 for the corresponding sell signals. Overall, the DefaultStrategy class provides a set of TA indicators and rules to determine buy and sell signals based on those indicators. Traders can use this strategy to backtest their trading ideas on the website you're building.
These indicators include ADX (Average Directional Index), AO (Awesome Oscillator), MACD (Moving Average Convergence Divergence), MFI (Money Flow Index), and others.
Some indicators are commented out, indicating that they are optional and can be uncommented if needed.
The function returns the DataFrame with all the mandatory indicators. The populate_buy_trend function populates the buy signal for the DataFrame based on the TA indicators. In this strategy, a buy signal is generated when the RSI (Relative Strength Index) is below 35, the fast %D (Stochastic Oscillator) is below 35, the ADX is above 30, and the plus DI (Directional Indicator) is above 0.5. Alternatively, a buy signal is also generated when the ADX is above 65 and the plus DI is above 0.5. The function modifies the DataFrame by adding a 'buy' column with a value of 1 for the corresponding buy signals. The populate_sell_trend function populates the sell signal for the DataFrame based on the TA indicators. In this strategy, a sell signal is generated when either the RSI or the fast %D crosses above 70, the ADX is above 10, and the minus DI is greater than 0. Alternatively, a sell signal is also generated when the ADX is above 70 and the minus DI is above 0.5. The function modifies the DataFrame by adding a 'sell' column with a value of 1 for the corresponding sell signals. Overall, the DefaultStrategy class provides a set of TA indicators and rules to determine buy and sell signals based on those indicators. Traders can use this strategy to backtest their trading ideas on the website you're building.
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_23.py", line 120, 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): 7716e60b15272feadd1b104bf2d7adc83a75e280d362bd1f6e961a47fb05b225 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: 2024-04-17 20:15:44