The given strategy, named E0V1E, involves a series of calculations and conditions to generate trading signals. Here's a breakdown of what the strategy does:
Populate Indicators: This step calculates various technical indicators using the input dataframe, such as Simple Moving Average (SMA), Commodity Channel Index (CTI), Relative Strength Index (RSI), Stochastic Fast, Exponential Moving Average (EMA), Bollinger Bands (BB), volume moving averages, Williams %R (r_14), Average Directional Index (ADX), and EWO (Elliott Wave Oscillator). Populate Entry Trend: In this step, the strategy defines different conditions to identify entry points for trades.
The conditions involve comparisons between various indicators and predefined threshold values.
If the conditions are met, a corresponding tag is assigned to the "enter_tag" column of the dataframe.
Populate Exit Trend: This step sets the exit conditions for the trades. Currently, it only assigns a value of 0 to the "exit_long" column and sets the "exit_tag" to "long_out" for all rows in the dataframe. Check Current Profit: This function is not a part of the strategy class but appears to be a separate function that checks the current profit of a trade and determines whether to sell or hold the position based on certain conditions. Overall, the strategy calculates various indicators, identifies entry conditions based on indicator thresholds, and sets basic exit conditions. The implementation of the exit conditions seems to be incomplete, as it only sets default values without any specific logic for exiting trades.
The conditions involve comparisons between various indicators and predefined threshold values.
If the conditions are met, a corresponding tag is assigned to the "enter_tag" column of the dataframe.
Populate Exit Trend: This step sets the exit conditions for the trades. Currently, it only assigns a value of 0 to the "exit_long" column and sets the "exit_tag" to "long_out" for all rows in the dataframe. Check Current Profit: This function is not a part of the strategy class but appears to be a separate function that checks the current profit of a trade and determines whether to sell or hold the position based on certain conditions. Overall, the strategy calculates various indicators, identifies entry conditions based on indicator thresholds, and sets basic exit conditions. The implementation of the exit conditions seems to be incomplete, as it only sets default values without any specific logic for exiting trades.
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: -0.1 timeframe: 5m hash(sha256): 73db21504280c3711386876b73c3c394dcf719aa8106a4eea894509988661cd8 indicators: upper EWO ema_200 close exit_long exit_tag volume_mean_12 fastk rsi_fast r_14 bb_middleband2 volume open fastd sma_15 bb_upperband2 volume_mean_24 mid bb_width ema_8 ema_16 cti ema_100 roc_1h adx roc lower rsi_slow rsi low bb_lowerband2 bb_width_1h
No similar strategies found. (based on used indicators)
last change: 2024-05-02 16:00:36