The BHV27v2 strategy is designed for trading and involves several indicators to make buy and sell decisions. Here's a simplified breakdown of its components and functionality:
Indicators:
RSI (Relative Strength Index): Measures the speed and change of price movements. EMA (Exponential Moving Average): Smoothed average of past prices.
ADX (Average Directional Index): Indicates the strength of a trend.
DI (Directional Indicator): Positive and negative components that help identify trend direction.
Fast and Slow SMAs (Simple Moving Averages): Averages of past prices with different time periods. Buy Condition: The strategy identifies potential buying opportunities based on various conditions: Price conditions related to highs, lows, and close prices. Comparison between various moving averages like fast and slow SMAs. ADX threshold conditions for trend strength. RSI conditions indicating potential reversals. Specific changes in trends and trend confirmations. Sell Condition: The strategy determines potential selling points based on conditions like: Reversal or slowdown in trend momentum. RSI and EMA conditions indicating potential overbought or bearish market conditions. Relationship between positive and negative directional indicators. Certain conditions related to the closing price, slow SMA, and trend changes. Note: The strategy's behavior changes depending on the runmode configuration, indicating different behaviors during normal run and hyperparameter optimization. Please be aware that this is a brief overview, and the actual strategy's behavior might be more complex due to interactions between these conditions and indicators. Always thoroughly test any trading strategy before applying it to real-world trading.
ADX (Average Directional Index): Indicates the strength of a trend.
DI (Directional Indicator): Positive and negative components that help identify trend direction.
Fast and Slow SMAs (Simple Moving Averages): Averages of past prices with different time periods. Buy Condition: The strategy identifies potential buying opportunities based on various conditions: Price conditions related to highs, lows, and close prices. Comparison between various moving averages like fast and slow SMAs. ADX threshold conditions for trend strength. RSI conditions indicating potential reversals. Specific changes in trends and trend confirmations. Sell Condition: The strategy determines potential selling points based on conditions like: Reversal or slowdown in trend momentum. RSI and EMA conditions indicating potential overbought or bearish market conditions. Relationship between positive and negative directional indicators. Certain conditions related to the closing price, slow SMA, and trend changes. Note: The strategy's behavior changes depending on the runmode configuration, indicating different behaviors during normal run and hyperparameter optimization. Please be aware that this is a brief overview, and the actual strategy's behavior might be more complex due to interactions between these conditions and indicators. Always thoroughly test any trading strategy before applying it to real-world trading.
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/BHV27v2.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): 3340c3abdeb17f753c740e676524e7f17e55ca42165c36cb2c8206a448ec2c57 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: 2024-05-07 19:41:15