The "BuyNStoploss" strategy is designed to backtest a trading strategy that involves buying a cryptocurrency pair within a specific price range and setting a stop loss to limit potential losses. Here's a breakdown of how the strategy works:
The strategy uses a 1-hour timeframe for analyzing price data. It has a predefined "minimal_roi" (minimal return on investment) parameter that specifies a fixed profit target of 10%.
The stop loss is set to -0.99, indicating a 99% loss threshold.
The strategy keeps track of certain flags, such as "bought_once," "stop_loss_once," "notify_buy," and "notify_stop_loss," to manage the execution of the strategy.
The "populate_indicators" function is responsible for populating indicators based on the price data. It also checks if the current price is within the specified buy zone range and triggers a buy signal if it meets the criteria. Similarly, if the price falls below the buy zone range, it triggers a sell signal as a stop loss measure. The "populate_buy_trend" function sets the "buy" column to 1 for the rows that meet the buy criteria. The "populate_sell_trend" function sets the "sell" column to 1 for the rows that meet the sell criteria. Overall, the strategy aims to buy a cryptocurrency pair when its price is within a specific range and sell it if the price falls below a certain threshold, acting as a stop loss. The strategy has a predefined profit target and uses flags to manage the execution and send notifications for buy and stop loss events.
The stop loss is set to -0.99, indicating a 99% loss threshold.
The strategy keeps track of certain flags, such as "bought_once," "stop_loss_once," "notify_buy," and "notify_stop_loss," to manage the execution of the strategy.
The "populate_indicators" function is responsible for populating indicators based on the price data. It also checks if the current price is within the specified buy zone range and triggers a buy signal if it meets the criteria. Similarly, if the price falls below the buy zone range, it triggers a sell signal as a stop loss measure. The "populate_buy_trend" function sets the "buy" column to 1 for the rows that meet the buy criteria. The "populate_sell_trend" function sets the "sell" column to 1 for the rows that meet the sell criteria. Overall, the strategy aims to buy a cryptocurrency pair when its price is within a specific range and sell it if the price falls below a certain threshold, acting as a stop loss. The strategy has a predefined profit target and uses flags to manage the execution and send notifications for buy and stop loss events.
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 57, in start_backtesting backtesting = Backtesting(config) ^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/optimize/backtesting.py", line 113, in __init__ self.strategylist.append(StrategyResolver.load_strategy(self.config)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/resolvers/strategy_resolver.py", line 48, in load_strategy strategy: IStrategy = StrategyResolver._load_strategy( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/resolvers/strategy_resolver.py", line 269, in _load_strategy strategy = StrategyResolver._load_object( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/freqtrade/freqtrade/resolvers/iresolver.py", line 156, in _load_object return module(**kwargs) ^^^^^^^^^^^^^^^^ File "/freqtrade/user_data/strategies/BuyNStoploss.py", line 25, in __init__ self.buy_zone_price_top = float(config['buy_zone_price_top']) ~~~~~~^^^^^^^^^^^^^^^^^^^^^^ KeyError: 'buy_zone_price_top'
stoploss: -0.99 timeframe: 1h hash(sha256): 17b1920a4b0bd92e536233940b0d1ce547db418238fd54b16a78ae034c3cae47 indicators: sell_criteria buy_criteria buy_zone_price_top buy_zone_price_bottom
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last change: 2024-04-28 00:15:57