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The "DryRunStrategy" is a trading strategy implemented in Python for backtesting purposes. It uses various technical indicators to generate buy and sell signals for a given financial instrument (e.g., a cryptocurrency). The strategy utilizes the following indicators:
Stochastic Oscillator (STOCH): It calculates the position of the current closing price relative to the high-low range over a specific period.
The "slowk" value from the oscillator is used in the strategy.
Relative Strength Index (RSI): It measures the magnitude of recent price changes to determine overbought or oversold conditions in the market.
The strategy uses the RSI value. Fisher Transform on RSI: It applies a mathematical transformation to the RSI values to normalize them between -1.0 and 1.0. Bollinger Bands: They are used to identify potential overbought and oversold levels. The strategy considers the lower Bollinger Band value. SAR Parabolic: It calculates trailing stop levels that can be used as a potential exit point. Hammer Candlestick Pattern (CDLHAMMER): It identifies a bullish reversal pattern in candlestick charts. The strategy's buy signal is generated when the following conditions are met: RSI is below 30 (indicating oversold conditions). Stochastic oscillator (slowk) is below 20. The closing price is below the lower Bollinger Band. A hammer candlestick pattern is detected. The strategy's sell signal is generated when the following conditions are met: The SAR Parabolic value is above the closing price. The Fisher Transform on RSI value is above 0.3. By backtesting this strategy on historical data, you can evaluate its performance and determine its effectiveness in generating profitable trading signals.
The "slowk" value from the oscillator is used in the strategy.
Relative Strength Index (RSI): It measures the magnitude of recent price changes to determine overbought or oversold conditions in the market.
The strategy uses the RSI value. Fisher Transform on RSI: It applies a mathematical transformation to the RSI values to normalize them between -1.0 and 1.0. Bollinger Bands: They are used to identify potential overbought and oversold levels. The strategy considers the lower Bollinger Band value. SAR Parabolic: It calculates trailing stop levels that can be used as a potential exit point. Hammer Candlestick Pattern (CDLHAMMER): It identifies a bullish reversal pattern in candlestick charts. The strategy's buy signal is generated when the following conditions are met: RSI is below 30 (indicating oversold conditions). Stochastic oscillator (slowk) is below 20. The closing price is below the lower Bollinger Band. A hammer candlestick pattern is detected. The strategy's sell signal is generated when the following conditions are met: The SAR Parabolic value is above the closing price. The Fisher Transform on RSI value is above 0.3. By backtesting this strategy on historical data, you can evaluate its performance and determine its effectiveness in generating profitable trading signals.
stoploss: -0.3 timeframe: 5m hash(sha256): 6b8d6473d068192904a9effd708fbaea377ed19b90b6b886d1dc52ffa500854d indicators: slowk lower fisher_rsi close rsi bb_lowerband CDLHAMMER sar
No similar strategies found. (based on used indicators)
last change: 2024-04-29 00:02:52