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The MaSuperStrategy is a trading strategy implemented in Python using the freqtrade library. Here's a short description of what this strategy does:
The strategy uses the populate_indicators method to calculate technical indicators for the given trading data. In this case, it adds the Relative Strength Index (RSI) and the Bollinger Bands indicator to the dataframe.
The RSI is calculated with a time period of 14, and the Bollinger Bands have a window of 20 and a standard deviation of 2.
The populate_buy_trend method is responsible for determining when to enter a buy trade.
It checks if the RSI is below 30 and if the closing price is below the lower Bollinger Band. If both conditions are met, a "buy" signal is generated for the corresponding data point. On the other hand, the populate_sell_trend method determines when to exit a buy trade and take profits. It checks if the RSI is above 50. If this condition is met, a "sell" signal is generated. The strategy also includes some parameters such as stoploss, which represents the maximum tolerated loss (in this case, 5%), and minimal_roi, which specifies the minimum desired return on investment (in this case, 1.5%). The ticker_interval parameter indicates the time interval used for the candlestick data, which is set to 1 minute in this case. The strategy keeps track of the number of times the populate_indicators, populate_buy_trend, and populate_sell_trend methods are called using the corresponding count variables. Additionally, the strategy includes print statements for debugging purposes, displaying the metadata and sample dataframes when the methods are called for the first time. Overall, the MaSuperStrategy uses the RSI and Bollinger Bands indicators to identify potential buy and sell signals based on specified conditions, aiming to capture profits while limiting losses.
The RSI is calculated with a time period of 14, and the Bollinger Bands have a window of 20 and a standard deviation of 2.
The populate_buy_trend method is responsible for determining when to enter a buy trade.
It checks if the RSI is below 30 and if the closing price is below the lower Bollinger Band. If both conditions are met, a "buy" signal is generated for the corresponding data point. On the other hand, the populate_sell_trend method determines when to exit a buy trade and take profits. It checks if the RSI is above 50. If this condition is met, a "sell" signal is generated. The strategy also includes some parameters such as stoploss, which represents the maximum tolerated loss (in this case, 5%), and minimal_roi, which specifies the minimum desired return on investment (in this case, 1.5%). The ticker_interval parameter indicates the time interval used for the candlestick data, which is set to 1 minute in this case. The strategy keeps track of the number of times the populate_indicators, populate_buy_trend, and populate_sell_trend methods are called using the corresponding count variables. Additionally, the strategy includes print statements for debugging purposes, displaying the metadata and sample dataframes when the methods are called for the first time. Overall, the MaSuperStrategy uses the RSI and Bollinger Bands indicators to identify potential buy and sell signals based on specified conditions, aiming to capture profits while limiting losses.
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 1401, in start min_date, max_date = self.backtest_one_strategy(strat, data, timerange) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1318, in backtest_one_strategy preprocessed = self.strategy.advise_all_indicators(data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, in advise_all_indicators return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1378, inreturn {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1410, in advise_indicators return self.populate_indicators(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/ma_super_strategy.py", line 19, in populate_indicators MaSuperStrategy.populate_indicators_count += 1 ^^^^^^^^^^^^^^^ NameError: name 'MaSuperStrategy' is not defined
stoploss: -0.05 timeframe: 1m hash(sha256): 6c68a83fb17be1f1c53ab8d1eec0c10b9ba8c2d6304a1cc4ef708fc9a1228751 indicators: lower bb_lowerband close rsi
No similar strategies found. (based on used indicators)
last change: 2024-04-29 00:31:18