The provided code snippet appears to define a trading strategy called "TeslaX" for backtesting purposes. This strategy is intended to generate buy and sell signals based on various technical indicators and conditions. Here's a brief description of what the strategy does:
The populate_indicators method is responsible for calculating and populating the necessary technical indicators used in the strategy.
These indicators include both informative indicators on a 15-minute timeframe and other indicators on the normal timeframe.
The populate_buy_trend method determines the conditions under which the strategy should generate buy signals.
It involves several sets of conditions that must be met simultaneously for a buy signal to be generated. These conditions include checks on various indicators such as moving averages, relative strength index (RSI), Elliott Wave Oscillator (EWO), and volume. The populate_sell_trend method defines the conditions for generating sell signals. Similar to the buy conditions, there are different conditions for selling, involving indicators like simple moving averages (SMA), exponential moving averages (EMA), and RSI. Additionally, the strategy includes a section that considers "don't buy" conditions, which are scenarios in which the strategy should avoid generating buy signals, even if other conditions are met. Overall, the strategy seems to be a complex combination of technical indicators and conditions, aiming to capture potential buy and sell opportunities in trading. Keep in mind that the specific details and effectiveness of the strategy would require a deeper understanding of the indicators used and the logic behind the conditions.
These indicators include both informative indicators on a 15-minute timeframe and other indicators on the normal timeframe.
The populate_buy_trend method determines the conditions under which the strategy should generate buy signals.
It involves several sets of conditions that must be met simultaneously for a buy signal to be generated. These conditions include checks on various indicators such as moving averages, relative strength index (RSI), Elliott Wave Oscillator (EWO), and volume. The populate_sell_trend method defines the conditions for generating sell signals. Similar to the buy conditions, there are different conditions for selling, involving indicators like simple moving averages (SMA), exponential moving averages (EMA), and RSI. Additionally, the strategy includes a section that considers "don't buy" conditions, which are scenarios in which the strategy should avoid generating buy signals, even if other conditions are met. Overall, the strategy seems to be a complex combination of technical indicators and conditions, aiming to capture potential buy and sell opportunities in trading. Keep in mind that the specific details and effectiveness of the strategy would require a deeper understanding of the indicators used and the logic behind the conditions.
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/TeslaX.py", line 322, in populate_indicators dataframe = self.normal_tf_indicators(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/TeslaX.py", line 271, in normal_tf_indicators dataframe['cti'] = pta.cti(dataframe["close"], length=20) ^^^ NameError: name 'pta' is not defined
stoploss: -0.07 timeframe: 5m hash(sha256): 0a0e57e1cd85b795b4da05af7582b941dba10b9b22141a895006a527d260d686 indicators: rsi_buy upper EWO vol_7_min ema_200 ewo_high roi close high_offset_2 ewo_low cti_mean ewo_high_2 tail roll_7 sell_signal bb_lowerband sell_rsi_main profit_threshold vol_ma_26 fastk bbdelta rsi_fast ma_sell_val vol_base ma_buy_val volume low_offset retries volumedataframevol_7_max closedelta high_offset low_offset_2 fastd volume_mean_slow vol_14_min base_nb_candles_buy vol_ma_200 sma_200 fast_d mid zlema2 rsi_fast_buy ___retries vol_7_max vol_ma_26_front base_nb_candles_sell hma_50 buy buy_tag ct
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last change: 2024-05-05 05:28:25