The BinHV27 strategy is a trading strategy that uses various technical indicators to generate buy and sell signals. Here is a summary of what the strategy does:
In the populate_indicators method:
Calculates the Relative Strength Index (RSI) with a time period of 5. Calculates the Exponential Moving Average (EMA) of the RSI with a time period of 5.
Calculates the Average Directional Index (ADX).
Calculates the Minus Directional Indicator (MINUS_DI).
Calculates the Plus Directional Indicator (PLUS_DI). Determines the "bigup" condition based on the comparison between the fast simple moving average (fastsma) and the slow simple moving average (slowsma) and a threshold condition. Determines the "bigdown" condition as the opposite of "bigup." Calculates the difference between the fastsma and slowsma as the trend. Determines the "preparechangetrend" condition based on the comparison of the current trend with the previous trend. Determines the "preparechangetrendconfirm" condition based on the "preparechangetrend" condition and an additional comparison with the trend two steps ago. Determines the "continueup" condition based on the comparison of the slowsma with its previous two values. Calculates the difference between the current and previous values of fastsma as delta. Determines the "slowingdown" condition based on the comparison of delta with its previous value. In the populate_buy_trend method: If the run mode is not set to 'hyperopt' (hyperparameter optimization): Calculates the EMA of the plusdi indicator with a user-defined time period. Calculates the EMA of the minusdi indicator with a user-defined time period. Calculates the EMA of the dataframe with a user-defined time period for the lowsma and highsma indicators. Calculates the SMA of the dataframe with a user-defined time period for the fastsma and slowsma indicators. Sets the "buy" signal when a set of conditions are met, including comparisons between different indicators and threshold values. In the populate_sell_trend method: If the run mode is not set to 'hyperopt' (hyperparameter optimization): Calculates the same indicators as in the populate_buy_trend method. Sets the "sell" signal when a set of conditions are met, including comparisons between different indicators and threshold values. The strategy uses indicators such as RSI, EMA, ADX, MINUS_DI, and PLUS_DI to identify potential buying and selling opportunities based on certain conditions. The conditions involve comparing various indicators and their values with user-defined parameters.
Calculates the Average Directional Index (ADX).
Calculates the Minus Directional Indicator (MINUS_DI).
Calculates the Plus Directional Indicator (PLUS_DI). Determines the "bigup" condition based on the comparison between the fast simple moving average (fastsma) and the slow simple moving average (slowsma) and a threshold condition. Determines the "bigdown" condition as the opposite of "bigup." Calculates the difference between the fastsma and slowsma as the trend. Determines the "preparechangetrend" condition based on the comparison of the current trend with the previous trend. Determines the "preparechangetrendconfirm" condition based on the "preparechangetrend" condition and an additional comparison with the trend two steps ago. Determines the "continueup" condition based on the comparison of the slowsma with its previous two values. Calculates the difference between the current and previous values of fastsma as delta. Determines the "slowingdown" condition based on the comparison of delta with its previous value. In the populate_buy_trend method: If the run mode is not set to 'hyperopt' (hyperparameter optimization): Calculates the EMA of the plusdi indicator with a user-defined time period. Calculates the EMA of the minusdi indicator with a user-defined time period. Calculates the EMA of the dataframe with a user-defined time period for the lowsma and highsma indicators. Calculates the SMA of the dataframe with a user-defined time period for the fastsma and slowsma indicators. Sets the "buy" signal when a set of conditions are met, including comparisons between different indicators and threshold values. In the populate_sell_trend method: If the run mode is not set to 'hyperopt' (hyperparameter optimization): Calculates the same indicators as in the populate_buy_trend method. Sets the "sell" signal when a set of conditions are met, including comparisons between different indicators and threshold values. The strategy uses indicators such as RSI, EMA, ADX, MINUS_DI, and PLUS_DI to identify potential buying and selling opportunities based on certain conditions. The conditions involve comparing various indicators and their values with user-defined parameters.
Traceback (most recent call last): File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexes/base.py", line 3791, in get_loc return self._engine.get_loc(casted_key) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "index.pyx", line 152, in pandas._libs.index.IndexEngine.get_loc File "index.pyx", line 181, in pandas._libs.index.IndexEngine.get_loc File "pandas/_libs/hashtable_class_helper.pxi", line 7080, in pandas._libs.hashtable.PyObjectHashTable.get_item File "pandas/_libs/hashtable_class_helper.pxi", line 7088, in pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: 'fastsma' The above exception was the direct cause of the following exception: 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/BinHV27_3.py", line 64, in populate_indicators dataframe['bigup'] = dataframe['fastsma'].gt(dataframe['slowsma']) & ((dataframe['fastsma'] - dataframe['slowsma']) > dataframe['close'] / 300) ~~~~~~~~~^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/frame.py", line 3893, in __getitem__ indexer = self.columns.get_loc(key) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ftuser/.local/lib/python3.11/site-packages/pandas/core/indexes/base.py", line 3798, in get_loc raise KeyError(key) from err KeyError: 'fastsma'
stoploss: -0.5 timeframe: 5m hash(sha256): b66873792fddc48464025eb48daa17bd30753e8391d8b67c7d000642097968c9 indicators: preparechangetrend close lowsma delta trend minusdi slowingdown continueup slowsma highsma bigdown emarsi bigup minusdiema adx plusdi fastsma preparechangetrendconfirm rsi runmode plusdiema
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last change: 2024-04-29 12:54:05