The provided strategy is a backtesting strategy for trading. It implements the IStrategy interface and has a few parameters defined for buying decisions. Here's a short description of what the strategy does:
The strategy uses a combination of moving averages, relative strength index (RSI), EWO (Elliott Wave Oscillator), and volume to make buying decisions.
It calculates various parameters for buying based on the specified ranges and defaults.
In the populate_buy_trend function, the strategy checks conditions for buying.
If the buy_32_ma_offset parameter is greater than the buy_33_ma_offset parameter and the buy_33_cti parameter is less than the buy_33_ewo parameter, it passes the conditions. Alternatively, if the buy_33_rsi parameter is less than the buy_33_volume parameter or the buy_33_ewo parameter is greater than the buy_33_rsi parameter, it also passes the conditions. In the populate_sell_trend function, no specific sell conditions are implemented, so it relies on the default behavior of the parent class. The populate_indicators function doesn't implement any additional indicators but calls the parent class function to populate indicators based on the provided dataframe and metadata. Overall, this strategy combines multiple parameters and conditions to determine buying opportunities based on moving averages, RSI, EWO, and volume.
It calculates various parameters for buying based on the specified ranges and defaults.
In the populate_buy_trend function, the strategy checks conditions for buying.
If the buy_32_ma_offset parameter is greater than the buy_33_ma_offset parameter and the buy_33_cti parameter is less than the buy_33_ewo parameter, it passes the conditions. Alternatively, if the buy_33_rsi parameter is less than the buy_33_volume parameter or the buy_33_ewo parameter is greater than the buy_33_rsi parameter, it also passes the conditions. In the populate_sell_trend function, no specific sell conditions are implemented, so it relies on the default behavior of the parent class. The populate_indicators function doesn't implement any additional indicators but calls the parent class function to populate indicators based on the provided dataframe and metadata. Overall, this strategy combines multiple parameters and conditions to determine buying opportunities based on moving averages, RSI, EWO, and volume.
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): 18e472e5d179cdd9aff841b4166b0bed8cfcc8b6abae4669b75b6540d360a8ee
Was not able to fetch indicators from Strategyfile.
last change: 2024-07-27 14:52:02