The TestStrategy is a backtesting strategy that aims to generate buy and sell signals based on technical analysis indicators. The strategy uses various TA (technical analysis) indicators to analyze the price data of a given trading pair. Here's a breakdown of the strategy:
Minimal ROI (Return on Investment): The strategy defines a minimal ROI that it aims to achieve.
In this case, the minimal ROI is set to 10, meaning the strategy expects a minimum return of 10 times the investment.
Stoploss: The strategy sets an optimal stoploss value to limit potential losses.
In this case, the stoploss is set to -0.99, which means that if the price falls by 99% of the entry price, the strategy will trigger a sell signal to cut losses. Timeframe: The strategy operates on a 1-minute timeframe, meaning it analyzes price data in 1-minute intervals. Trailing Stoploss: The strategy has a trailing stoploss feature, which is currently disabled. Trailing stoploss is a dynamic stoploss level that adjusts as the price moves in favor of the trade. Process Only New Candles: The strategy determines whether to populate indicators only for new candles or for the entire historical data. In this case, it is set to False, meaning indicators will be calculated for the entire historical data. Use Sell Signal: The strategy utilizes a sell signal to determine when to sell a position. This feature is enabled. Sell Profit Only: The strategy sells the position only when it is in profit. This means that it aims to maximize profits and avoid selling at a loss. Ignore ROI if Buy Signal: The strategy can ignore the minimal ROI requirement if a buy signal is generated. In this case, it is set to False, meaning the ROI requirement is always considered. Order Types: The strategy defines the order types for different actions. For buy and sell orders, it uses a limit order type, while for stoploss, it uses a market order type. Informative Pairs: The strategy can define additional non-tradeable pair/interval combinations for caching from the exchange. These combinations provide additional information but are not used for actual trading. Populate Indicators: This function is responsible for adding various TA indicators to the price data. Currently, it returns the original dataframe without adding any indicators. Populate Buy Trend: This function populates the buy signal based on specific indices in the dataframe. It sets the 'buy' column to 1 at the specified indices, indicating a buy signal. Populate Sell Trend: This function populates the sell signal based on specific indices in the dataframe. It sets the 'sell' column to 1 at the specified indices, indicating a sell signal. Overall, the TestStrategy backtesting strategy defines the minimal ROI, stoploss, timeframe, and other parameters for generating buy and sell signals based on TA indicators. It also provides functions for populating the buy and sell signals in the price data.
In this case, the minimal ROI is set to 10, meaning the strategy expects a minimum return of 10 times the investment.
Stoploss: The strategy sets an optimal stoploss value to limit potential losses.
In this case, the stoploss is set to -0.99, which means that if the price falls by 99% of the entry price, the strategy will trigger a sell signal to cut losses. Timeframe: The strategy operates on a 1-minute timeframe, meaning it analyzes price data in 1-minute intervals. Trailing Stoploss: The strategy has a trailing stoploss feature, which is currently disabled. Trailing stoploss is a dynamic stoploss level that adjusts as the price moves in favor of the trade. Process Only New Candles: The strategy determines whether to populate indicators only for new candles or for the entire historical data. In this case, it is set to False, meaning indicators will be calculated for the entire historical data. Use Sell Signal: The strategy utilizes a sell signal to determine when to sell a position. This feature is enabled. Sell Profit Only: The strategy sells the position only when it is in profit. This means that it aims to maximize profits and avoid selling at a loss. Ignore ROI if Buy Signal: The strategy can ignore the minimal ROI requirement if a buy signal is generated. In this case, it is set to False, meaning the ROI requirement is always considered. Order Types: The strategy defines the order types for different actions. For buy and sell orders, it uses a limit order type, while for stoploss, it uses a market order type. Informative Pairs: The strategy can define additional non-tradeable pair/interval combinations for caching from the exchange. These combinations provide additional information but are not used for actual trading. Populate Indicators: This function is responsible for adding various TA indicators to the price data. Currently, it returns the original dataframe without adding any indicators. Populate Buy Trend: This function populates the buy signal based on specific indices in the dataframe. It sets the 'buy' column to 1 at the specified indices, indicating a buy signal. Populate Sell Trend: This function populates the sell signal based on specific indices in the dataframe. It sets the 'sell' column to 1 at the specified indices, indicating a sell signal. Overall, the TestStrategy backtesting strategy defines the minimal ROI, stoploss, timeframe, and other parameters for generating buy and sell signals based on TA indicators. It also provides functions for populating the buy and sell signals in the price data.
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: 'buy' 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 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 1391, in ft_advise_signals dataframe = self.advise_entry(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 1425, in advise_entry df = self.populate_entry_trend(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/strategy/interface.py", line 225, in populate_entry_trend return self.populate_buy_trend(dataframe, metadata) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/Discord_TestStrategy.py", line 91, in populate_buy_trend dataframe.iloc[i, dataframe.columns.get_loc('buy')] = 1 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 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: 'buy'
stoploss: -0.99 timeframe: 1m hash(sha256): fdc914c03d0320ffc4b95551684cc26188ef851c896f31e52f07a4a34ee725fb
Was not able to fetch indicators from Strategyfile.
last change: 2024-07-27 00:15:20