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The strategy, named "CombinedBinHAndClucV8Hyper," is implemented as a class that inherits from the base strategy class "IStrategy." The strategy consists of several methods that perform different tasks. populate_indicators:
This method takes a DataFrame and metadata as input and returns a modified DataFrame. It populates the indicators for the strategy by calling two other indicator methods (informative_1h_indicators and normal_tf_indicators) and merging the results into the original DataFrame.
populate_buy_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame.
It defines multiple conditions that need to be met for a buy signal to be generated.
Each condition is represented as a logical expression involving various DataFrame columns and threshold values. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'buy' column. populate_sell_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame. It defines conditions for a sell signal to be generated. The conditions involve comparing the current and previous values of certain columns, such as 'close' and 'bb_upperband', and checking the value of the 'rsi' column. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'sell' column. Overall, the strategy applies various technical analysis indicators and conditions to generate buy and sell signals based on the provided DataFrame's price and volume data.
populate_buy_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame.
It defines multiple conditions that need to be met for a buy signal to be generated.
Each condition is represented as a logical expression involving various DataFrame columns and threshold values. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'buy' column. populate_sell_trend: This method takes a DataFrame and metadata as input and returns a modified DataFrame. It defines conditions for a sell signal to be generated. The conditions involve comparing the current and previous values of certain columns, such as 'close' and 'bb_upperband', and checking the value of the 'rsi' column. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'sell' column. Overall, the strategy applies various technical analysis indicators and conditions to generate buy and sell signals based on the provided DataFrame's price and volume data.
startup_candle_count : 200 ema_50_1h: 0.001% ema_100_1h: -0.041%
Unable to parse Traceback (Logfile Exceeded Limit)
stoploss: -0.99 timeframe: 5m hash(sha256): 83df28a8955afe2e6035071dbdc07bcfd9cbad7f1120028e2fe8eb465832d7a5 indicators: sma_200_1h upper ema_200 ema_50 close sma_5 tail bb_lowerband mfi ema_200_1h bbdelta volume smaHigh ATR ema_100_1h ssl_up closedelta sslDown open hlv volume_mean_slow ema_50_1h smaLow sma_200 high sslUp mid ssl_down_1h ssl_down rsi_1h ema_100 lower ema_12 bb_middleband rsi sma_200_dec bb_upperband ema_slow ema_26 low ssl_up_1h sma_200_dec_1h
Similar Strategies: (based on used indicators)
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last change: 2024-08-02 09:11:57