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The "BuyAllSellAllStrategy" is a trading strategy implemented in Python using the Freqtrade library. It is designed to backtest and simulate trading based on a simple set of rules. Key features of the strategy include:
ROI (Return on Investment) Table: The strategy defines a table that specifies the expected returns at different time intervals.
For example, it expects a 15.4% return at time 0, 7.4% return at 18 units of time, 3.9% return at 50 units of time, and 2% return at 165 units of time.
Stop Loss: The strategy sets a stop loss at -5.1%.
If the trade goes below this threshold, it will trigger a sell signal to cut losses. Timeframe: The strategy operates on 5-minute candlestick data. Trailing Stop: The strategy uses a trailing stop mechanism, which means it dynamically adjusts the stop loss level as the trade progresses. It sets a positive trailing stop value of 0.9% and an offset of 1.5% to reduce false triggers. It will only trigger the trailing stop if the offset is reached. Sell Signal: The strategy utilizes a sell signal to determine when to sell. It sets the option to use a sell signal to True. It sells not only for profit but also to cut losses. The profit offset is set at 1% to ensure a minimum profit before selling. Buy Signal: The strategy generates a random buy signal for each candle. It assigns a random value of either 0 or 1 to the "buy" column in the input dataframe. Sell Signal Implementation: The strategy sets the "sell" column in the input dataframe to 0, indicating no sell signal is generated. Custom Sell Function: There is a commented out custom sell function that can be used to implement a custom selling logic based on additional conditions and data analysis. Overall, the strategy randomly generates buy signals and uses a trailing stop mechanism along with a sell signal to determine when to sell. The ROI table and stop loss provide guidelines for expected returns and risk management.
For example, it expects a 15.4% return at time 0, 7.4% return at 18 units of time, 3.9% return at 50 units of time, and 2% return at 165 units of time.
Stop Loss: The strategy sets a stop loss at -5.1%.
If the trade goes below this threshold, it will trigger a sell signal to cut losses. Timeframe: The strategy operates on 5-minute candlestick data. Trailing Stop: The strategy uses a trailing stop mechanism, which means it dynamically adjusts the stop loss level as the trade progresses. It sets a positive trailing stop value of 0.9% and an offset of 1.5% to reduce false triggers. It will only trigger the trailing stop if the offset is reached. Sell Signal: The strategy utilizes a sell signal to determine when to sell. It sets the option to use a sell signal to True. It sells not only for profit but also to cut losses. The profit offset is set at 1% to ensure a minimum profit before selling. Buy Signal: The strategy generates a random buy signal for each candle. It assigns a random value of either 0 or 1 to the "buy" column in the input dataframe. Sell Signal Implementation: The strategy sets the "sell" column in the input dataframe to 0, indicating no sell signal is generated. Custom Sell Function: There is a commented out custom sell function that can be used to implement a custom selling logic based on additional conditions and data analysis. Overall, the strategy randomly generates buy signals and uses a trailing stop mechanism along with a sell signal to determine when to sell. The ROI table and stop loss provide guidelines for expected returns and risk management.
startup_candle_count : 50 Recursive Analysis found no issues while using 50 startup_candle_count
Biased Entry Signals:
11Biased Exit Signals:
5
stoploss: -0.051 timeframe: 5m hash(sha256): 6b2b7a1e83e92103b18a2f5fa8627b41b8dc75676513c642c88fbfcbe2723317 indicators: sell buy
No similar strategies found. (based on used indicators)
last change: 2023-02-08 10:44:03