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The HyperoptableStrategy class is a trading strategy that utilizes various technical analysis (TA) indicators to make buy and sell decisions. The strategy consists of three main methods: populate_indicators, populate_buy_trend, and populate_sell_trend. The populate_indicators method adds several TA indicators to the given DataFrame.
These indicators include ADX (Average Directional Index), MACD (Moving Average Convergence Divergence), Minus DI, Plus DI, RSI (Relative Strength Index), Stochastic Fast, Bollinger Bands, and EMA (Exponential Moving Average).
By populating the DataFrame with these indicators, they become available for use in the strategy's buy and sell signal calculations.
The populate_buy_trend method calculates the buy signal based on the values of the TA indicators. The buy signal conditions include a low RSI value (self.buy_rsi.value), a low Stochastic Fast value (below 35), a high ADX value (above 30), and a high Plus DI value (self.buy_plusdi.value). If these conditions are met, the 'buy' column in the DataFrame is set to 1, indicating a buy signal. The populate_sell_trend method calculates the sell signal based on the values of the TA indicators. The sell signal conditions include a crossed above condition for RSI (self.sell_rsi.value) or Stochastic Fast (above 70), a high ADX value (above 10), and a high Minus DI value (self.sell_minusdi.value). If these conditions are met, the 'sell' column in the DataFrame is set to 1, indicating a sell signal. Overall, the HyperoptableStrategy class populates the DataFrame with various TA indicators, uses them to determine buy and sell signals based on specified conditions, and returns the modified DataFrame with the corresponding 'buy' and 'sell' columns.
These indicators include ADX (Average Directional Index), MACD (Moving Average Convergence Divergence), Minus DI, Plus DI, RSI (Relative Strength Index), Stochastic Fast, Bollinger Bands, and EMA (Exponential Moving Average).
By populating the DataFrame with these indicators, they become available for use in the strategy's buy and sell signal calculations.
The populate_buy_trend method calculates the buy signal based on the values of the TA indicators. The buy signal conditions include a low RSI value (self.buy_rsi.value), a low Stochastic Fast value (below 35), a high ADX value (above 30), and a high Plus DI value (self.buy_plusdi.value). If these conditions are met, the 'buy' column in the DataFrame is set to 1, indicating a buy signal. The populate_sell_trend method calculates the sell signal based on the values of the TA indicators. The sell signal conditions include a crossed above condition for RSI (self.sell_rsi.value) or Stochastic Fast (above 70), a high ADX value (above 10), and a high Minus DI value (self.sell_minusdi.value). If these conditions are met, the 'sell' column in the DataFrame is set to 1, indicating a sell signal. Overall, the HyperoptableStrategy class populates the DataFrame with various TA indicators, uses them to determine buy and sell signals based on specified conditions, and returns the modified DataFrame with the corresponding 'buy' and 'sell' columns.
stoploss: -0.1 timeframe: 5m hash(sha256): f7540dbc6356dce3f044b7631f460e23f026ce6ba0c15cde4e0259ecfd1dffe2 indicators: macdsignal upper adx minus_di lower mid fastk bb_middleband rsi macd bb_lowerband bb_upperband plus_di fastd ema10 macdhist
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last change: 2023-07-05 05:08:30