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The NASOSv4 strategy is a trading strategy that aims to generate buy and sell signals based on various indicators. Here is a breakdown of what the strategy does:
populate_indicators: This method populates the indicators used by the strategy. It takes a DataFrame and metadata as inputs and returns a DataFrame with additional indicator columns.
populate_buy_trend: This method identifies buy signals based on specific conditions.
It checks various indicators and sets the 'buy' and 'buy_tag' columns in the DataFrame to indicate a buy signal.
The strategy checks conditions such as the RSI (Relative Strength Index), close price, moving averages, EWO (Elliott Wave Oscillator), and volume to determine if a buy signal should be triggered. Multiple buy conditions are checked, and if any of them are met, the 'buy' and 'buy_tag' columns are set to indicate a buy signal. populate_sell_trend: This method identifies sell signals based on specific conditions. It checks various indicators and sets the 'sell' column in the DataFrame to indicate a sell signal. The strategy checks conditions such as the close price, moving averages, RSI, and volume to determine if a sell signal should be triggered. Multiple sell conditions are checked, and if any of them are met, the 'sell' column is set to indicate a sell signal. Overall, the NASOSv4 strategy uses a combination of indicators such as RSI, moving averages, and volume to generate buy and sell signals in a backtesting scenario.
populate_buy_trend: This method identifies buy signals based on specific conditions.
It checks various indicators and sets the 'buy' and 'buy_tag' columns in the DataFrame to indicate a buy signal.
The strategy checks conditions such as the RSI (Relative Strength Index), close price, moving averages, EWO (Elliott Wave Oscillator), and volume to determine if a buy signal should be triggered. Multiple buy conditions are checked, and if any of them are met, the 'buy' and 'buy_tag' columns are set to indicate a buy signal. populate_sell_trend: This method identifies sell signals based on specific conditions. It checks various indicators and sets the 'sell' column in the DataFrame to indicate a sell signal. The strategy checks conditions such as the close price, moving averages, RSI, and volume to determine if a sell signal should be triggered. Multiple sell conditions are checked, and if any of them are met, the 'sell' column is set to indicate a sell signal. Overall, the NASOSv4 strategy uses a combination of indicators such as RSI, moving averages, and volume to generate buy and sell signals in a backtesting scenario.
startup_candle_count : 200 hma_50: -0.001% ema_100: 0.014% rsi_slow: 0.002%
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: -0.15 timeframe: 5m hash(sha256): cba0e22c708be5e3a0fb7dd4fd6beb78eb88575b2b45b111a7eb600ea7dba992 indicators: rsi_buy EWO ewo_high ewo_low high_offset_2 close ewo_high_2 sell_signal profit_threshold rsi_fast ma_sell_val ma_buy_val volume low_offset retries high_offset low_offset_2 base_nb_candles_buy ___retries base_nb_candles_sell hma_50 buy buy_tag sma_9 ema_100 lookback_candles max_slippage rsi_slow rsi low close_1h
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last change: 2023-12-02 00:40:18