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The "SwingHighToSky" strategy is designed for backtesting trading strategies on a 15-minute timeframe. It uses the Commodity Channel Index (CCI) and Relative Strength Index (RSI) indicators to generate buy and sell signals. The strategy defines certain parameters for the CCI and RSI indicators:
CCI buy time period (cciBuyTP) is set to 72, and the buy value (cciBuyVal) is set to -175.
CCI sell time period (cciSellTP) is set to 66, and the sell value (cciSellVal) is set to -106.
RSI buy time period (rsiBuyTP) is set to 36, and the buy value (rsiBuyVal) is set to 90.
RSI sell time period (rsiSellTP) is set to 45, and the sell value (rsiSellVal) is set to 88. The strategy populates these indicators in the provided DataFrame using the populate_indicators function. It calculates the CCI and RSI values for the specified time periods and adds them as additional columns to the DataFrame. To generate buy signals, the populate_buy_trend function sets the 'buy' column in the DataFrame to 1 when both the CCI value (for the specified buy time period) is below the buy value and the RSI value (for the specified buy time period) is below the buy value. Similarly, the populate_sell_trend function sets the 'sell' column to 1 when both the CCI value (for the specified sell time period) is above the sell value and the RSI value (for the specified sell time period) is above the sell value. The strategy also defines a stop loss value of -0.34338 and a minimal return on investment (ROI) configuration. The minimal ROI is defined as a dictionary with time periods as keys and corresponding ROI values. Overall, the "SwingHighToSky" strategy aims to identify potential buying opportunities when the CCI and RSI values are below certain thresholds and selling opportunities when the CCI and RSI values are above certain thresholds.
CCI sell time period (cciSellTP) is set to 66, and the sell value (cciSellVal) is set to -106.
RSI buy time period (rsiBuyTP) is set to 36, and the buy value (rsiBuyVal) is set to 90.
RSI sell time period (rsiSellTP) is set to 45, and the sell value (rsiSellVal) is set to 88. The strategy populates these indicators in the provided DataFrame using the populate_indicators function. It calculates the CCI and RSI values for the specified time periods and adds them as additional columns to the DataFrame. To generate buy signals, the populate_buy_trend function sets the 'buy' column in the DataFrame to 1 when both the CCI value (for the specified buy time period) is below the buy value and the RSI value (for the specified buy time period) is below the buy value. Similarly, the populate_sell_trend function sets the 'sell' column to 1 when both the CCI value (for the specified sell time period) is above the sell value and the RSI value (for the specified sell time period) is above the sell value. The strategy also defines a stop loss value of -0.34338 and a minimal return on investment (ROI) configuration. The minimal ROI is defined as a dictionary with time periods as keys and corresponding ROI values. Overall, the "SwingHighToSky" strategy aims to identify potential buying opportunities when the CCI and RSI values are below certain thresholds and selling opportunities when the CCI and RSI values are above certain thresholds.
stoploss: -0.343 timeframe: 15m hash(sha256): 23839e7db496d01f70c3013a9948269589531ec7891c0ac3c1c8074db9e00ba9 indicators: rsistrrsiSellTP ccistrcciSellTP rsistrrsiBuyTP ccistrcciBuyTP
No similar strategies found. (based on used indicators)
last change: 2023-09-22 00:13:36