The MultiRSI strategy is a trading strategy that uses multiple Relative Strength Index (RSI) indicators to make buy and sell decisions. Here's a breakdown of how the strategy works:
The strategy calculates two Simple Moving Averages (SMA) - a shorter-term SMA with a time period of 5 and a longer-term SMA with a time period of 200. The strategy then resamples the dataframes to create two additional dataframes - one with a ticker interval twice the original interval and another with a ticker interval eight times the original interval.
RSI values are calculated for both the shorter-term and longer-term resampled dataframes using a time period of 14.
The resampled dataframes are merged back with the original dataframe.
The RSI is calculated again for the merged dataframe. Any missing values in the dataframe are filled using the forward-fill method. The buy signal is generated when the following conditions are met: The shorter-term SMA is greater than or equal to the longer-term SMA. The RSI is lower than the RSI of the longer-term resampled dataframe minus 20. The sell signal is generated when the following conditions are met: The RSI is higher than the RSI of the shorter-term resampled dataframe. The RSI is higher than the RSI of the longer-term resampled dataframe. The strategy sets a minimal return on investment (ROI) of 0.01 and a stop-loss of -0.05. It uses a ticker interval of 5 minutes. Please note that this is a brief description of the strategy, and there may be additional implementation details or considerations not mentioned here.
RSI values are calculated for both the shorter-term and longer-term resampled dataframes using a time period of 14.
The resampled dataframes are merged back with the original dataframe.
The RSI is calculated again for the merged dataframe. Any missing values in the dataframe are filled using the forward-fill method. The buy signal is generated when the following conditions are met: The shorter-term SMA is greater than or equal to the longer-term SMA. The RSI is lower than the RSI of the longer-term resampled dataframe minus 20. The sell signal is generated when the following conditions are met: The RSI is higher than the RSI of the shorter-term resampled dataframe. The RSI is higher than the RSI of the longer-term resampled dataframe. The strategy sets a minimal return on investment (ROI) of 0.01 and a stop-loss of -0.05. It uses a ticker interval of 5 minutes. Please note that this is a brief description of the strategy, and there may be additional implementation details or considerations not mentioned here.
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/MultiRSI_136.py", line 33, in populate_indicators dataframe_short = resample_to_interval(dataframe, self.get_ticker_indicator() * 2) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/MultiRSI_136.py", line 26, in get_ticker_indicator return int(self.ticker_interval) ^^^^^^^^^^^^^^^^^^^^^^^^^ ValueError: invalid literal for int() with base 10: '5m'
stoploss: -0.05 timeframe: 5m hash(sha256): abfbe2cec613d6574b6c89a3bd707f9ad1a91c06e1fe142daa01b0ad27f417e1 indicators: sma5 _long _short _shortrsi rsi _longrsi sma200
No similar strategies found. (based on used indicators)
last change: 2024-04-28 15:31:11