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The BB_RPB_TSL_v104 strategy is a trading strategy implemented as a class that inherits from the IStrategy base class. It contains several methods to perform various operations. The populate_indicators method takes a DataFrame and metadata as input and returns a modified DataFrame.
It applies indicators specific to the strategy on the input DataFrame, including informative indicators derived from a 1-hour timeframe.
The resulting DataFrame is merged with the original DataFrame using a specified timeframe.
The populate_buy_trend method populates the buy signals in the DataFrame based on various conditions. It creates an empty column called 'buy_tag' in the DataFrame. It then defines multiple boolean conditions using DataFrame column values and strategy parameters. These conditions check for specific patterns or criteria indicative of a buy signal. If a condition is met, the corresponding 'buy_tag' is assigned to the respective row in the DataFrame. The strategy includes various conditions to identify potential buy signals, such as checking for dips, breaks, local uptrends, local dips, EWO (Elliott Wave Oscillator) values, reverse deadfish patterns, clucHA patterns, cofi (Cobra Fast Indicator) signals, gumbo patterns, and NFI (New Fish Index) patterns. Overall, the strategy aims to generate buy signals based on specific technical indicators and patterns observed in the market data.
It applies indicators specific to the strategy on the input DataFrame, including informative indicators derived from a 1-hour timeframe.
The resulting DataFrame is merged with the original DataFrame using a specified timeframe.
The populate_buy_trend method populates the buy signals in the DataFrame based on various conditions. It creates an empty column called 'buy_tag' in the DataFrame. It then defines multiple boolean conditions using DataFrame column values and strategy parameters. These conditions check for specific patterns or criteria indicative of a buy signal. If a condition is met, the corresponding 'buy_tag' is assigned to the respective row in the DataFrame. The strategy includes various conditions to identify potential buy signals, such as checking for dips, breaks, local uptrends, local dips, EWO (Elliott Wave Oscillator) values, reverse deadfish patterns, clucHA patterns, cofi (Cobra Fast Indicator) signals, gumbo patterns, and NFI (New Fish Index) patterns. Overall, the strategy aims to generate buy signals based on specific technical indicators and patterns observed in the market data.
stoploss: -0.99 timeframe: 5m hash(sha256): 6b7bff5a1a3dc89b808935a85ceb99d4a02fc1f5579de20fb0f74d0aefb283ea indicators: upper close volume_mean_12 ema_200_1h rsi_fast r_480_1h volume xe1 ema_20 source ha_closedelta momdiv_coh bb_upperband2 volume_mean_24 high ema_8 r_480 cci bb_lowerband3 rsi_1h xe6 final_ub momdiv_col ha_high pm adx ema_12 T3Average ema_slow ema_26 bb_width_1h bb_lowerband2_40 cmf_1h bb_upperband2_40 basic_ub sma_21 momdiv_buy bb_middleband2 closedelta sma_15 ha_open volume_mean_4 cmf rmi_length_val lower roc T3 r_32 rsi T3_1h xe3 momdiv_sell crsi_1h bb_middleband3 bb_upperband3 ema_50 tail mfi
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last change: 2022-09-02 09:14:17