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The strategy, named "CombinedBinHAndClucV8Hyper," is implemented as a class that inherits from the base strategy class "IStrategy." The strategy consists of several methods that perform different tasks. populate_indicators:
This method takes a DataFrame and metadata as input and returns a modified DataFrame. It populates the indicators for the strategy by calling two other indicator methods (informative_1h_indicators and normal_tf_indicators) and merging the results into the original DataFrame.
populate_buy_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame.
It defines multiple conditions that need to be met for a buy signal to be generated.
Each condition is represented as a logical expression involving various DataFrame columns and threshold values. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'buy' column. populate_sell_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame. It defines conditions for a sell signal to be generated. The conditions involve comparing the current and previous values of certain columns, such as 'close' and 'bb_upperband', and checking the value of the 'rsi' column. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'sell' column. Overall, the strategy applies various technical analysis indicators and conditions to generate buy and sell signals based on the provided DataFrame's price and volume data.
populate_buy_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame.
It defines multiple conditions that need to be met for a buy signal to be generated.
Each condition is represented as a logical expression involving various DataFrame columns and threshold values. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'buy' column. populate_sell_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame. It defines conditions for a sell signal to be generated. The conditions involve comparing the current and previous values of certain columns, such as 'close' and 'bb_upperband', and checking the value of the 'rsi' column. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'sell' column. Overall, the strategy applies various technical analysis indicators and conditions to generate buy and sell signals based on the provided DataFrame's price and volume data.
startup_candle_count : 200 ema_50_1h: 0.001% ema_100_1h: -0.041%
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 1364, in start self.load_bt_data_detail() File "/freqtrade/freqtrade/optimize/backtesting.py", line 266, in load_bt_data_detail self.detail_data = history.load_data( ^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/data/history/history_utils.py", line 99, in load_data hist = load_pair_history(pair=pair, timeframe=timeframe, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/data/history/history_utils.py", line 57, in load_pair_history return data_handler.ohlcv_load(pair=pair, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/data/history/idatahandler.py", line 319, in ohlcv_load pairdf = self._ohlcv_load( ^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/data/history/featherdatahandler.py", line 62, in _ohlcv_load pairdata = read_feather(filename) ^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/io/feather_format.py", line 148, in read_feather return feather.read_feather( ^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pyarrow/feather.py", line 226, in read_feather return (read_table( ^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pyarrow/feather.py", line 252, in read_table reader = _feather.FeatherReader( ^^^^^^^^^^^^^^^^^^^^^^^ File "pyarrow/_feather.pyx", line 79, in pyarrow._feather.FeatherReader.__cinit__ File "pyarrow/error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: Not an Arrow file
stoploss: -0.99 timeframe: 5m hash(sha256): 83df28a8955afe2e6035071dbdc07bcfd9cbad7f1120028e2fe8eb465832d7a5 indicators: sma_200_1h upper ema_200 ema_50 close sma_5 tail bb_lowerband mfi ema_200_1h bbdelta volume smaHigh ATR ema_100_1h ssl_up closedelta sslDown open hlv volume_mean_slow ema_50_1h smaLow sma_200 high sslUp mid ssl_down_1h ssl_down rsi_1h ema_100 lower ema_12 bb_middleband rsi sma_200_dec bb_upperband ema_slow ema_26 low ssl_up_1h sma_200_dec_1h
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last change: 2024-03-01 00:33:53