The CofiBitStrategy is a trading strategy designed for backtesting on a website. Here's a short description of what the strategy does:
It uses technical indicators to make buy and sell decisions based on the given dataframe. The strategy calculates various indicators such as Stochastic Fast, Exponential Moving Averages (EMA), and Average Directional Index (ADX) using the TA-Lib library.
The populate_indicators function adds these calculated indicators to the dataframe.
The populate_buy_trend function determines the buy signal based on the following conditions: The opening price is below the EMA low.
The fast %K line crosses above the fast %D line. The fast %K and %D values are below 30. The ADX value is above 30. If these conditions are met, the 'buy' column in the dataframe is set to 1. The populate_sell_trend function determines the sell signal based on the following conditions: The opening price is above or equal to the EMA high. Either the fast %K or %D line crosses above 70. If any of these conditions are met, the 'sell' column in the dataframe is set to 1. By using these indicators and conditions, the strategy aims to generate profitable trading signals for the given dataset.
The populate_indicators function adds these calculated indicators to the dataframe.
The populate_buy_trend function determines the buy signal based on the following conditions: The opening price is below the EMA low.
The fast %K line crosses above the fast %D line. The fast %K and %D values are below 30. The ADX value is above 30. If these conditions are met, the 'buy' column in the dataframe is set to 1. The populate_sell_trend function determines the sell signal based on the following conditions: The opening price is above or equal to the EMA high. Either the fast %K or %D line crosses above 70. If any of these conditions are met, the 'sell' column in the dataframe is set to 1. By using these indicators and conditions, the strategy aims to generate profitable trading signals for the given dataset.
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/CofiBitStrategy.py", line 28, in populate_indicators stoch_fast = ta.STOCHF(dataframe, 5.0, 3.0, 0.0, 3.0, 0.0) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "talib/_abstract.pxi", line 444, in talib._ta_lib.Function.__call__ File "talib/_abstract.pxi", line 310, in talib._ta_lib.Function.set_function_args File "talib/_abstract.pxi", line 513, in talib._ta_lib.Function.__check_opt_input_value TypeError: Invalid parameter value for fastk_period (expected int, got float)
stoploss: -0.25 timeframe: 5m hash(sha256): a11a51d6dc398c8a4cbc180ac07e623907c78c8f281977c4493f5ef8e9dd41e5 indicators: ema_close adx ema_high open ema_low fastd fastk
No similar strategies found. (based on used indicators)
last change: 2024-07-27 00:00:16