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The KeltnerRSIdos strategy is a trading strategy that uses Keltner Channels and the Relative Strength Index (RSI) to determine buy and sell signals. Here's a breakdown of its key components:
Timeframe: The strategy operates on daily candlestick data. Stoploss: The stop loss parameter is set to -0.254, indicating a maximum tolerated loss before triggering a sell signal.
Minimal ROI: The minimal return on investment (ROI) is set to 100, indicating that the strategy will hold onto assets indefinitely until the ROI reaches this threshold.
Use Exit Signal: The strategy utilizes an exit signal to determine when to sell, rather than relying solely on the stop loss or ROI.
Ignore ROI if Entry Signal: The strategy does not consider the ROI when determining the entry signal. Hyperopt Spaces: The strategy includes three hyperparameters that can be optimized using hyperopt: window_range, atrs_range, and rsi_buy_hline. These parameters control the parameters for the Keltner Channels and RSI. Populate Indicators: This function calculates the Keltner Channels and RSI values for the given dataframe. It iterates over different window sizes and atrs values to populate multiple indicator columns. Populate Buy Trend: This function determines the buy signals based on two conditions. The first condition checks if the closing price crosses above the upper Keltner Band, and the second condition checks if the RSI value is above a specified threshold. Populate Sell Trend: This function determines the sell signals based on a single condition. It checks if the closing price crosses below the middle Keltner Band. Overall, the strategy aims to identify potential buying opportunities when the price crosses above the upper Keltner Band and the RSI is above a certain threshold. It generates sell signals when the price crosses below the middle Keltner Band.
Minimal ROI: The minimal return on investment (ROI) is set to 100, indicating that the strategy will hold onto assets indefinitely until the ROI reaches this threshold.
Use Exit Signal: The strategy utilizes an exit signal to determine when to sell, rather than relying solely on the stop loss or ROI.
Ignore ROI if Entry Signal: The strategy does not consider the ROI when determining the entry signal. Hyperopt Spaces: The strategy includes three hyperparameters that can be optimized using hyperopt: window_range, atrs_range, and rsi_buy_hline. These parameters control the parameters for the Keltner Channels and RSI. Populate Indicators: This function calculates the Keltner Channels and RSI values for the given dataframe. It iterates over different window sizes and atrs values to populate multiple indicator columns. Populate Buy Trend: This function determines the buy signals based on two conditions. The first condition checks if the closing price crosses above the upper Keltner Band, and the second condition checks if the RSI value is above a specified threshold. Populate Sell Trend: This function determines the sell signals based on a single condition. It checks if the closing price crosses below the middle Keltner Band. Overall, the strategy aims to identify potential buying opportunities when the price crosses above the upper Keltner Band and the RSI is above a certain threshold. It generates sell signals when the price crosses below the middle Keltner Band.
stoploss: -0.254 timeframe: 5m hash(sha256): 2db00b53b74bad06ae8dd8bc145056bd57425812db2410fe65a88164ad89728a indicators: f"kc_middleband_windows_atrss close rsi f"kc_upperband_windows_atrss
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last change: 2022-07-11 00:25:04