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The "DoesNothingStrategy" is a basic trading strategy implemented in Python for backtesting purposes. It serves as a skeleton or template for building more complex strategies. This strategy has the following key features:
ROI (Return on Investment): The minimal ROI (return on investment) for this strategy is set to 0.01.
It is a customizable parameter that can be adjusted based on market conditions.
A low ROI is recommended for quick turnarounds.
Stoploss: The optimal stoploss for this strategy is set to -0.25. A stoploss is a predetermined level at which a trade will be closed to limit potential losses. Timeframe: The strategy is designed to operate on a 5-minute timeframe. The timeframe represents the interval at which the strategy analyzes price data and makes trading decisions. The strategy consists of three main methods: populate_indicators: This method is responsible for populating technical indicators on the provided dataframe. However, in this particular strategy, it returns the original dataframe without any additional indicators. populate_buy_trend: This method identifies buy signals and populates the 'buy' column of the dataframe accordingly. In this case, the buy conditions are left empty, so no specific criteria are defined for entering a buy trade. populate_sell_trend: This method identifies sell signals and populates the 'sell' column of the dataframe accordingly. Similar to the buy method, no specific sell conditions are defined in this strategy. Overall, this strategy doesn't implement any specific trading logic or rules. It simply serves as a starting point for developing more advanced strategies by providing the necessary structure and placeholders for indicator calculations, buy signals, and sell signals.
It is a customizable parameter that can be adjusted based on market conditions.
A low ROI is recommended for quick turnarounds.
Stoploss: The optimal stoploss for this strategy is set to -0.25. A stoploss is a predetermined level at which a trade will be closed to limit potential losses. Timeframe: The strategy is designed to operate on a 5-minute timeframe. The timeframe represents the interval at which the strategy analyzes price data and makes trading decisions. The strategy consists of three main methods: populate_indicators: This method is responsible for populating technical indicators on the provided dataframe. However, in this particular strategy, it returns the original dataframe without any additional indicators. populate_buy_trend: This method identifies buy signals and populates the 'buy' column of the dataframe accordingly. In this case, the buy conditions are left empty, so no specific criteria are defined for entering a buy trade. populate_sell_trend: This method identifies sell signals and populates the 'sell' column of the dataframe accordingly. Similar to the buy method, no specific sell conditions are defined in this strategy. Overall, this strategy doesn't implement any specific trading logic or rules. It simply serves as a starting point for developing more advanced strategies by providing the necessary structure and placeholders for indicator calculations, buy signals, and sell signals.
stoploss: -0.25 timeframe: 5m hash(sha256): 00638d0c4697481b093b503e367f8be3b2020eb3f67a7905b076fd8b999635af
Was not able to fetch indicators from Strategyfile.
last change: 2023-06-30 11:51:33