The SmoothOperator strategy is a trading strategy implemented as a class in Python. Here's a brief description of what the strategy does:
populate_indicators function:
Resamples the input dataframe to a specified interval and resample factor. Calculates various technical indicators such as CCI (Commodity Channel Index), RSI (Relative Strength Index), ADX (Average Directional Index), MFI (Money Flow Index), and their corresponding exponential moving averages (EMA).
Calculates Bollinger Bands for volatility analysis.
Calculates MACD (Moving Average Convergence Divergence) and its components.
Calculates additional Bollinger Bands for entry conditions. Computes other derived indicators like percentage of price within Bollinger Bands, Bollinger Band sharpness, smoothed Bollinger Band sharpness, a combination of MFI, RSI, and CCI, and their triple exponential moving average (TEMA). Calculates candle size and the average of open, high, low, and close prices. Computes simple moving averages (SMA) with different time periods. populate_buy_trend function: Identifies buy signals based on specific conditions, including previous average price behavior, Bollinger Bands, CCI, RSI, and MFI values. Sets a 'buy' flag to 1 for identified buy signals. populate_sell_trend function: Identifies sell signals based on specific conditions, including the smoothed combination of MFI, RSI, and CCI values, consecutive green candles, and high values of CCI and RSI. Sets a 'sell' flag to 1 for identified sell signals. The StrategyHelper class likely contains additional helper functions that are used within the SmoothOperator strategy but are not explicitly described in the provided code snippet.
Calculates Bollinger Bands for volatility analysis.
Calculates MACD (Moving Average Convergence Divergence) and its components.
Calculates additional Bollinger Bands for entry conditions. Computes other derived indicators like percentage of price within Bollinger Bands, Bollinger Band sharpness, smoothed Bollinger Band sharpness, a combination of MFI, RSI, and CCI, and their triple exponential moving average (TEMA). Calculates candle size and the average of open, high, low, and close prices. Computes simple moving averages (SMA) with different time periods. populate_buy_trend function: Identifies buy signals based on specific conditions, including previous average price behavior, Bollinger Bands, CCI, RSI, and MFI values. Sets a 'buy' flag to 1 for identified buy signals. populate_sell_trend function: Identifies sell signals based on specific conditions, including the smoothed combination of MFI, RSI, and CCI values, consecutive green candles, and high values of CCI and RSI. Sets a 'sell' flag to 1 for identified sell signals. The StrategyHelper class likely contains additional helper functions that are used within the SmoothOperator strategy but are not explicitly described in the provided code snippet.
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/SmoothOperator.py", line 41, in populate_indicators dataframe = StrategyHelper.resample(dataframe, self.ticker_interval, self.resample_factor) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/SmoothOperator.py", line 312, in resample df = df.resample(str(int(interval[:-1]) * factor) + 'min', plotoschow=ohlc_dict) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: NDFrame.resample() got an unexpected keyword argument 'plotoschow'
stoploss: -0.05 timeframe: 5m hash(sha256): 85e353eed6b875cb9ea97b7f94f09a0442949ead4e596b73931ca0eb6252bcf3 indicators: mfi_rsi_cci_smooth mfi_smooth upper close entry_bb_middleband mfi bb_lowerband macdhist bsharp_medium entry_bb_upperband bsharp sma_slow average date sma_fast open bsharp_slow entry_bb_lowerband high macdsignal cci_smooth mid rsi_smooth cci sma_medium macd bsharp_fast open high low close candle_size adx lower bpercent bb_middleband rsi bb_upperband low resample_sma
Similar Strategies: (based on used indicators)
Strategy: SmoothOperator_10, Similarity Score: 97.56%
Strategy: SmoothOperator_2, Similarity Score: 97.56%
Strategy: SmoothOperator_3, Similarity Score: 97.56%
Strategy: SmoothOperator_4, Similarity Score: 97.56%
Strategy: chl, Similarity Score: 97.56%
Strategy: sample_strategy4, Similarity Score: 97.56%
Strategy: strategy_test, Similarity Score: 97.56%
Strategy: SmoothOperator_213, Similarity Score: 92.68%
last change: 2024-07-26 22:39:33