The MyStrategyTemplate is a trading strategy implemented in Python for backtesting on a website. Here's a breakdown of what the strategy does:
Timeframe and Candle Count:
The strategy operates on 5-minute candle data. It requires a startup candle count of 30 before generating valid signals.
ROI and Stop Loss: The strategy aims for a minimal return on investment (ROI) of 0.99 (99%).
It sets a stop loss at -10% to limit potential losses.
Plotting: The strategy can plot indicators on a chart after backtesting. The main plot includes a Simple Moving Average (SMA) in blue color. The subplots include the Relative Strength Index (RSI) in red color. Indicators: The strategy uses the Keltner Channel indicator provided by the "qtpylib" library. It calculates the upper, lower, and middle bands of the Keltner Channel. It computes the percentage of the close price between the lower and upper bands. It calculates the width of the Keltner Channel as a ratio of the middle band. Buy Settings: The strategy needs to define the conditions for buying. Currently, the conditions are left empty and need to be implemented. Sell Settings: The strategy needs to define the conditions for selling, excluding ROI take profit. Currently, the conditions are left empty and need to be implemented. Please note that the code provided is a template, and the empty sections need to be filled with appropriate conditions for buying and selling based on the desired trading strategy.
ROI and Stop Loss: The strategy aims for a minimal return on investment (ROI) of 0.99 (99%).
It sets a stop loss at -10% to limit potential losses.
Plotting: The strategy can plot indicators on a chart after backtesting. The main plot includes a Simple Moving Average (SMA) in blue color. The subplots include the Relative Strength Index (RSI) in red color. Indicators: The strategy uses the Keltner Channel indicator provided by the "qtpylib" library. It calculates the upper, lower, and middle bands of the Keltner Channel. It computes the percentage of the close price between the lower and upper bands. It calculates the width of the Keltner Channel as a ratio of the middle band. Buy Settings: The strategy needs to define the conditions for buying. Currently, the conditions are left empty and need to be implemented. Sell Settings: The strategy needs to define the conditions for selling, excluding ROI take profit. Currently, the conditions are left empty and need to be implemented. Please note that the code provided is a template, and the empty sections need to be filled with appropriate conditions for buying and selling based on the desired trading strategy.
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 1335, in backtest_one_strategy results = self.backtest( ^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 1213, in backtest data: Dict = self._get_ohlcv_as_lists(processed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 381, in _get_ohlcv_as_lists df_analyzed = self.strategy.ft_advise_signals(pair_data, {'pair': pair}) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1392, in ft_advise_signals dataframe = self.advise_exit(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1444, in advise_exit if 'exit_long' not in df.columns: ^^^^^^^^^^ AttributeError: 'NoneType' object has no attribute 'columns'
stoploss: -0.1 timeframe: 5m hash(sha256): c64bb36647b197636c94a99486dfc221c28c41c4f85c4c86df0196306546f29b indicators: kc_middleband kc_lowerband close kc_upperband kc_width kc_percent
No similar strategies found. (based on used indicators)
last change: 2024-04-29 20:55:17