The BinHV27 strategy is a trading strategy that utilizes various technical indicators to determine buy and sell signals. Here is a short description of what the strategy does:
Populates indicators: The strategy calculates and adds several technical indicators to the input dataframe, including RSI (Relative Strength Index), EMA (Exponential Moving Average), ADX (Average Directional Index), MINUS_DI, PLUS_DI, and various moving averages. Populates buy trend: Based on the populated indicators and a set of defined parameters for buying, the strategy identifies potential buy signals in the dataframe.
The buy conditions include criteria such as the current slow moving average being greater than 0, the closing price being lower than the highsma and lowsma, the minusdi being greater than the minusdiema, and the RSI being greater than or equal to its previous value.
Additionally, the buy conditions incorporate different combinations of ADX, bigup, bigdown, and emarsi values based on the specified parameters.
Populates sell trend: Similar to the buy trend, the strategy populates sell signals in the dataframe based on specific sell parameters. The sell conditions include criteria such as the preparechangetrendconfirm not being true, the continueup not being true, the closing price being higher than the lowsma or highsma, the highsma being greater than 0, and various combinations of ADX, emarsi, bigup, bigdown, slowingdown, minusdi, and plusdi values based on the specified parameters. Override for default ROI table functionality: The strategy provides a custom implementation for calculating the return on investment (ROI) based on different decay types (linear, exponential, or fitting). It calculates the minimum ROI based on the specified decay type and the trade duration. Overall, the strategy combines multiple indicators and their corresponding parameters to generate buy and sell signals, and also provides flexibility in customizing the ROI calculation.
The buy conditions include criteria such as the current slow moving average being greater than 0, the closing price being lower than the highsma and lowsma, the minusdi being greater than the minusdiema, and the RSI being greater than or equal to its previous value.
Additionally, the buy conditions incorporate different combinations of ADX, bigup, bigdown, and emarsi values based on the specified parameters.
Populates sell trend: Similar to the buy trend, the strategy populates sell signals in the dataframe based on specific sell parameters. The sell conditions include criteria such as the preparechangetrendconfirm not being true, the continueup not being true, the closing price being higher than the lowsma or highsma, the highsma being greater than 0, and various combinations of ADX, emarsi, bigup, bigdown, slowingdown, minusdi, and plusdi values based on the specified parameters. Override for default ROI table functionality: The strategy provides a custom implementation for calculating the return on investment (ROI) based on different decay types (linear, exponential, or fitting). It calculates the minimum ROI based on the specified decay type and the trade duration. Overall, the strategy combines multiple indicators and their corresponding parameters to generate buy and sell signals, and also provides flexibility in customizing the ROI calculation.
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stoploss: -0.5 timeframe: 5m hash(sha256): 55ac4eba3d71870bf8bf28f0c73bccefdee0e08d9adb068b09b8fbe7b560abfc indicators: preparechangetrend endpct close decaytype lowsma fittype startpct emarsi3 delta emarsi2 trend minusdi adx2 slowingdown continueup emarsi4 slowsma highsma bigdown emarsi emarsi1 decayrate bigup minusdiema adx plusdi fastsma preparechangetrendconfirm adx3 rsi adx1 decaytime adx4 plusdiema enabled
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last change: 2024-07-28 02:28:31