Not Enough Data to display!
Average Overall
| Not Enough Data! / Avg statistics not populated yet. |
|---|
The RSI_BB strategy is a trading strategy that uses the Relative Strength Index (RSI) and Bollinger Bands indicators to generate buy and sell signals. Here's a breakdown of what the strategy does:
Import necessary libraries and modules:
talib.abstract as ta: A library for technical analysis indicators. pandas: A library for data manipulation and analysis.
DataFrame: A class from pandas used to store and manipulate data.
qtpylib.indicators from freqtrade.vendor: A library for additional indicators used in the strategy.
IStrategy from freqtrade.strategy.interface: An interface for creating trading strategies. Define the strategy class RSI_BB that inherits from IStrategy. Set the ticker_interval to '1d', indicating that the strategy operates on daily price data. Define the minimal_roi table, which specifies the minimum return on investment (ROI) targets at different time intervals. The strategy aims to achieve an ROI of 0.85 at time 0, 0.407 at time 11343, 0.16 at time 23766, and 0 at time 41495. Set the stoploss value to -1, indicating that the strategy does not use a fixed stop-loss level. Implement the populate_indicators function, which calculates the RSI and Bollinger Bands indicators based on the price data. The RSI is stored in the 'rsi' column of the dataframe, while the lower and upper Bollinger Bands with standard deviations of 1 and 3 are stored in the 'bb_lowerband1' and 'bb_upperband3' columns, respectively. Implement the populate_buy_trend function, which generates buy signals based on the condition that the closing price is below the lower Bollinger Band. Implement the populate_sell_trend function, which generates sell signals based on the condition that the RSI is greater than 56 and the closing price is above the upper Bollinger Band. The strategy aims to buy when the price is low (below the lower Bollinger Band) and sell when the price is high (above the upper Bollinger Band) while considering the RSI as an additional confirmation indicator.
DataFrame: A class from pandas used to store and manipulate data.
qtpylib.indicators from freqtrade.vendor: A library for additional indicators used in the strategy.
IStrategy from freqtrade.strategy.interface: An interface for creating trading strategies. Define the strategy class RSI_BB that inherits from IStrategy. Set the ticker_interval to '1d', indicating that the strategy operates on daily price data. Define the minimal_roi table, which specifies the minimum return on investment (ROI) targets at different time intervals. The strategy aims to achieve an ROI of 0.85 at time 0, 0.407 at time 11343, 0.16 at time 23766, and 0 at time 41495. Set the stoploss value to -1, indicating that the strategy does not use a fixed stop-loss level. Implement the populate_indicators function, which calculates the RSI and Bollinger Bands indicators based on the price data. The RSI is stored in the 'rsi' column of the dataframe, while the lower and upper Bollinger Bands with standard deviations of 1 and 3 are stored in the 'bb_lowerband1' and 'bb_upperband3' columns, respectively. Implement the populate_buy_trend function, which generates buy signals based on the condition that the closing price is below the lower Bollinger Band. Implement the populate_sell_trend function, which generates sell signals based on the condition that the RSI is greater than 56 and the closing price is above the upper Bollinger Band. The strategy aims to buy when the price is low (below the lower Bollinger Band) and sell when the price is high (above the upper Bollinger Band) while considering the RSI as an additional confirmation indicator.
startup_candle_count : 50 rsi: -6.336%
stoploss: -1 timeframe: 1d hash(sha256): 63ee53240ed48fed85bffec4b401aa91f0659ade597548c30a4d8f5d90e780b6 indicators: upper lower bb_upperband3 bb_lowerband1 close rsi
No similar strategies found. (based on used indicators)
last change: 2023-12-03 00:17:11