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The "BbandRsi" strategy is a trading strategy that combines Bollinger Bands and Relative Strength Index (RSI) indicators to generate buy and sell signals. Here's a breakdown of how the strategy works:
The strategy uses a 1-hour timeframe for analyzing price data. It calculates the RSI indicator with a time period of 14 using the close prices of the assets.
It also calculates the Bollinger Bands with a window of 20 and 2 standard deviations from the typical price.
The lower Bollinger Band is stored in the 'bb_lowerband' column of the dataframe.
The middle Bollinger Band is stored in the 'bb_middleband' column. The upper Bollinger Band is stored in the 'bb_upperband' column. Additionally, it calculates the 10-period Exponential Moving Average (EMA) and stores it in the 'ema10' column. The strategy determines a buy signal when both of the following conditions are met: The RSI value is below 30 (indicating oversold conditions). The closing price is below the lower Bollinger Band. The 'buy' column in the dataframe is set to 1 to indicate the buy signal. The strategy determines a sell signal when the RSI value is above 70 (indicating overbought conditions). The 'sell' column in the dataframe is set to 1 to indicate the sell signal. The strategy's minimal return on investment (ROI) is set to 0.015, and the stop-loss is set to -0.03. These values can be adjusted based on market conditions. The strategy uses a startup candle count of 14, meaning it requires at least 14 candles of historical data to generate signals. Overall, this strategy aims to identify potential buying opportunities when the price is below the lower Bollinger Band and the RSI is in oversold territory, and selling opportunities when the RSI is in overbought territory.
It also calculates the Bollinger Bands with a window of 20 and 2 standard deviations from the typical price.
The lower Bollinger Band is stored in the 'bb_lowerband' column of the dataframe.
The middle Bollinger Band is stored in the 'bb_middleband' column. The upper Bollinger Band is stored in the 'bb_upperband' column. Additionally, it calculates the 10-period Exponential Moving Average (EMA) and stores it in the 'ema10' column. The strategy determines a buy signal when both of the following conditions are met: The RSI value is below 30 (indicating oversold conditions). The closing price is below the lower Bollinger Band. The 'buy' column in the dataframe is set to 1 to indicate the buy signal. The strategy determines a sell signal when the RSI value is above 70 (indicating overbought conditions). The 'sell' column in the dataframe is set to 1 to indicate the sell signal. The strategy's minimal return on investment (ROI) is set to 0.015, and the stop-loss is set to -0.03. These values can be adjusted based on market conditions. The strategy uses a startup candle count of 14, meaning it requires at least 14 candles of historical data to generate signals. Overall, this strategy aims to identify potential buying opportunities when the price is below the lower Bollinger Band and the RSI is in oversold territory, and selling opportunities when the RSI is in overbought territory.
stoploss: -0.03 timeframe: 1h hash(sha256): 94b849f1d32fffd1fc9a3a2e9f7f8041691e7f39b81aba2bc31a84e6af13cd83 indicators: upper mid lower bb_middleband rsi close bb_upperband bb_lowerband price_up ema10
No similar strategies found. (based on used indicators)
last change: 2023-06-24 10:26:53