The BBRSI_Final strategy is a trading strategy that uses Bollinger Bands and the Relative Strength Index (RSI) to generate buy and sell signals. Here's a breakdown of what the strategy does:
populate_indicators function:
This function calculates and adds several technical indicators to the given DataFrame. It calculates the RSI using the ta.RSI function and adds it as a column named 'rsi'.
It calculates Bollinger Bands with different standard deviations (2, 1, and 3) using the qtpylib.bollinger_bands function.
It adds the lower, middle, and upper bands of each set of Bollinger Bands as separate columns in the DataFrame.
populate_buy_trend function: This function populates the 'buy' column in the DataFrame based on the buy conditions of the strategy. The buy condition in this case is when the closing price is below the lower band of the Bollinger Bands with a standard deviation of 1. If the condition is met, the 'buy' column is set to 1 for that particular row. populate_sell_trend function: This function populates the 'sell' column in the DataFrame based on the sell conditions of the strategy. The sell condition in this case is when the closing price is above the lower band of the Bollinger Bands with a standard deviation of 1. If the condition is met, the 'sell' column is set to 1 for that particular row. Overall, the strategy uses Bollinger Bands to identify potential entry and exit points in the market based on the price crossing the lower band. The RSI indicator is calculated but not directly used in generating the buy or sell signals in this implementation.
It calculates Bollinger Bands with different standard deviations (2, 1, and 3) using the qtpylib.bollinger_bands function.
It adds the lower, middle, and upper bands of each set of Bollinger Bands as separate columns in the DataFrame.
populate_buy_trend function: This function populates the 'buy' column in the DataFrame based on the buy conditions of the strategy. The buy condition in this case is when the closing price is below the lower band of the Bollinger Bands with a standard deviation of 1. If the condition is met, the 'buy' column is set to 1 for that particular row. populate_sell_trend function: This function populates the 'sell' column in the DataFrame based on the sell conditions of the strategy. The sell condition in this case is when the closing price is above the lower band of the Bollinger Bands with a standard deviation of 1. If the condition is met, the 'sell' column is set to 1 for that particular row. Overall, the strategy uses Bollinger Bands to identify potential entry and exit points in the market based on the price crossing the lower band. The RSI indicator is calculated but not directly used in generating the buy or sell signals in this implementation.
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: 30m hash(sha256): 5c2abc7ce7f9fdce43dddef94ab908ba59ffd9446e0ba4cd8078229ed1c1f112 indicators: upper mid lower bb_lowerband1 bb_upperband1 bb_middleband3 bb_upperband3 bb_middleband rsi bb_middleband1 close bb_upperband bb_lowerband bb_lowerband3
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last change: 2024-04-29 00:48:58