The ReinforcedAverageStrategy is a trading strategy that buys and sells assets based on crossover signals. It is a proof of concept strategy and may not perform well in real-world trading. Here are the important parts of the strategy:
Minimal ROI: The minimal return on investment (ROI) designed for the strategy is set to 0.5.
This means that the strategy aims to achieve at least a 0.5% return on each trade.
Stoploss: The optimal stop loss for the strategy is set to -0.2.
If the price of an asset drops by 0.2% from the purchase price, the strategy will sell the asset to limit losses. Ticker interval: The strategy is designed to work with a ticker interval of 4 hours. It analyzes price data at 4-hour intervals. Trailing stoploss: The strategy does not use a trailing stop loss, which means it does not dynamically adjust the stop loss level as the price changes. Populate indicators: This function calculates technical indicators such as the exponential moving averages (EMA), Bollinger Bands, and simple moving averages (SMA) on the price data. Populate buy trend: This function determines the buy signals based on the crossover of the short-term EMA and the medium-term EMA. It also checks if the price is above a certain moving average (resample_2880_sma) and if the trading volume is greater than zero. Populate sell trend: This function determines the sell signals based on the crossover of the medium-term EMA and the short-term EMA. It only considers the trading volume to be greater than zero. Please note that this strategy is intended as a proof of concept and may not be suitable for actual trading purposes.
This means that the strategy aims to achieve at least a 0.5% return on each trade.
Stoploss: The optimal stop loss for the strategy is set to -0.2.
If the price of an asset drops by 0.2% from the purchase price, the strategy will sell the asset to limit losses. Ticker interval: The strategy is designed to work with a ticker interval of 4 hours. It analyzes price data at 4-hour intervals. Trailing stoploss: The strategy does not use a trailing stop loss, which means it does not dynamically adjust the stop loss level as the price changes. Populate indicators: This function calculates technical indicators such as the exponential moving averages (EMA), Bollinger Bands, and simple moving averages (SMA) on the price data. Populate buy trend: This function determines the buy signals based on the crossover of the short-term EMA and the medium-term EMA. It also checks if the price is above a certain moving average (resample_2880_sma) and if the trading volume is greater than zero. Populate sell trend: This function determines the sell signals based on the crossover of the medium-term EMA and the short-term EMA. It only considers the trading volume to be greater than zero. Please note that this strategy is intended as a proof of concept and may not be suitable for actual trading purposes.
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 113, in __init__ self.strategylist.append(StrategyResolver.load_strategy(self.config)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/resolvers/strategy_resolver.py", line 48, in load_strategy strategy: IStrategy = StrategyResolver._load_strategy( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/resolvers/strategy_resolver.py", line 269, in _load_strategy strategy = StrategyResolver._load_object( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/resolvers/iresolver.py", line 156, in _load_object return module(**kwargs) ^^^^^^^^^^^^^^^^ TypeError: ReinforcedAverageStrategy_92.__init__() got an unexpected keyword argument 'config'
stoploss: -0.2 timeframe: 4h hash(sha256): 2a6f66f12f1dd370878ef47c4d4095f71568500c23bb4e7213511a9e32464478 indicators: upper mid lower volume _long maMedium close bb_middleband resample_2880_sma _longsma maShort bb_upperband bb_lowerband sma
No similar strategies found. (based on used indicators)
last change: 2024-04-29 13:10:14