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The "ONUR" strategy is a trading strategy implemented in Python using the Freqtrade library. Here is a short description of what the strategy does:
The strategy uses the following indicators:
RSI (Relative Strength Index): Calculates the RSI indicator with a time period of 14. Bollinger Bands: Calculates the Bollinger Bands indicator with a window of 20 and 2 standard deviations.
The strategy defines the following parameters: minimal_roi: Specifies the minimum return on investment for different time periods.
stoploss: Sets the stop loss threshold at -0.99.
trailing_stop: Enables trailing stop functionality. trailing_stop_positive: Sets the positive threshold for trailing stop at 0.293. trailing_stop_positive_offset: Sets the offset for trailing stop positive threshold at 0.362. trailing_only_offset_is_reached: Enables trailing stop only when offset is reached. timeframe: Sets the timeframe for the strategy to 15 minutes. order_types: Specifies the order types for different trading actions. The strategy implements the following methods: populate_indicators: Populates the RSI and Bollinger Bands indicators on the input dataframe. populate_buy_trend: Populates the 'buy' signal on the dataframe based on certain conditions involving RSI and the middle Bollinger Band. populate_sell_trend: Populates the 'sell' signal on the dataframe based on certain conditions (currently commented out). Overall, the strategy aims to generate buy signals when the RSI is below 74 and the closing price is above the middle Bollinger Band. The sell signals are currently not implemented in the provided code snippet.
The strategy defines the following parameters: minimal_roi: Specifies the minimum return on investment for different time periods.
stoploss: Sets the stop loss threshold at -0.99.
trailing_stop: Enables trailing stop functionality. trailing_stop_positive: Sets the positive threshold for trailing stop at 0.293. trailing_stop_positive_offset: Sets the offset for trailing stop positive threshold at 0.362. trailing_only_offset_is_reached: Enables trailing stop only when offset is reached. timeframe: Sets the timeframe for the strategy to 15 minutes. order_types: Specifies the order types for different trading actions. The strategy implements the following methods: populate_indicators: Populates the RSI and Bollinger Bands indicators on the input dataframe. populate_buy_trend: Populates the 'buy' signal on the dataframe based on certain conditions involving RSI and the middle Bollinger Band. populate_sell_trend: Populates the 'sell' signal on the dataframe based on certain conditions (currently commented out). Overall, the strategy aims to generate buy signals when the RSI is below 74 and the closing price is above the middle Bollinger Band. The sell signals are currently not implemented in the provided code snippet.
startup_candle_count : 50 rsi: 3.032%
stoploss: -0.99 timeframe: 15m hash(sha256): 9f8513da455c78b71e76581be1dfe41ed480cf174a0dc99303d213f1cf34d68e indicators: upper mid lower bb_middleband rsi close bb_upperband bb_lowerband
No similar strategies found. (based on used indicators)
last change: 2023-06-29 02:19:51