The "TaSearchLevelG15m" strategy is a backtesting strategy implemented in Python. It is designed to analyze trading data and make decisions based on various indicators. Here is a breakdown of its functionality:
The strategy first populates a DataFrame with different indicators such as RSI (Relative Strength Index), minimum and maximum levels, and buy signals for short and long positions.
It calculates the local minimum and maximum values using the argrelextrema function.
For each local minimum, it checks if certain conditions are met and logs relevant information if they are.
It also checks for long and short signals based on specific conditions and logs the information accordingly. The strategy calculates the difference between two values and performs actions based on the difference. It populates entry and exit signals based on the calculated indicators and conditions. The leverage for the strategy is set to 10. The strategy returns the calculated difference. Overall, the strategy aims to identify potential buying and selling opportunities based on the given indicators and conditions.
It calculates the local minimum and maximum values using the argrelextrema function.
For each local minimum, it checks if certain conditions are met and logs relevant information if they are.
It also checks for long and short signals based on specific conditions and logs the information accordingly. The strategy calculates the difference between two values and performs actions based on the difference. It populates entry and exit signals based on the calculated indicators and conditions. The leverage for the strategy is set to 10. The strategy returns the calculated difference. Overall, the strategy aims to identify potential buying and selling opportunities based on the given indicators and conditions.
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 57, in start_backtesting backtesting = Backtesting(config) ^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 114, in __init__ validate_config_consistency(self.config) File "/freqtrade/freqtrade/configuration/config_validation.py", line 95, in validate_config_consistency validate_config_schema(conf, preliminary=preliminary) File "/freqtrade/freqtrade/configuration/config_validation.py", line 65, in validate_config_schema raise ValidationError( jsonschema.exceptions.ValidationError: 'stoploss' is a required property
stoploss: 0 timeframe: 5m hash(sha256): 6792c9aa1356dfa47215f47311bad3ba0c14a8d837a9df5ade42ffa9c663468a indicators: high buy_short2 min_level buy_long max_x close i_low i_open buy_short i_close buy_long2 i_high low max_local open rsi_7 max_level min_local
Similar Strategies: (based on used indicators)
Strategy: TaSearchLevelG15m2, Similarity Score: 94.74%
Strategy: TaSearchLevelG15m_2, Similarity Score: 94.74%
Strategy: TaSearchLevelG15m_3, Similarity Score: 94.74%
Strategy: TaSearchLevelG15m_4, Similarity Score: 94.74%
Strategy: TaSearchLevelG15m_emhanced, Similarity Score: 94.74%
Strategy: TaSearchLevelG15mv, Similarity Score: 94.74%
Strategy: TaSearchLevelH15m, Similarity Score: 94.74%
Strategy: TaSearchLevelH15m2, Similarity Score: 94.74%
Strategy: TaSearchLevelH15m_2, Similarity Score: 94.74%
Strategy: myfubin, Similarity Score: 94.74%
last change: 2024-04-29 20:51:53