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The strategy, called CombinedBinHAndClucV8, is implemented as a class that inherits from the IStrategy class. It consists of three main functions: populate_indicators, populate_buy_trend, and populate_sell_trend. populate_indicators function:
This function takes a DataFrame and a metadata dictionary as inputs and returns a modified DataFrame.
It calls two other functions, informative_1h_indicators and normal_tf_indicators, to populate additional indicators in the DataFrame.
The merge_informative_pair function is used to merge the informative 1-hour indicators with the current timeframe indicators.
The modified DataFrame is then returned. populate_buy_trend function: This function takes a DataFrame and a metadata dictionary as inputs and returns a modified DataFrame. It defines multiple sets of conditions using boolean expressions, each representing a potential buy signal. The conditions check various indicators, such as moving averages (ema), bollinger bands (bb), relative strength index (rsi), and volume, to determine if a buy signal is present. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'buy' column. The modified DataFrame is then returned. populate_sell_trend function: This function takes a DataFrame and a metadata dictionary as inputs and returns a modified DataFrame. It defines two sets of conditions using boolean expressions, representing potential sell signals. The conditions check the price surpassing the upper Bollinger band and the relative strength index (rsi) reaching a certain value. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'sell' column. The modified DataFrame is then returned. Overall, the strategy combines various technical indicators to generate buy and sell signals based on specific conditions in the market.
It calls two other functions, informative_1h_indicators and normal_tf_indicators, to populate additional indicators in the DataFrame.
The merge_informative_pair function is used to merge the informative 1-hour indicators with the current timeframe indicators.
The modified DataFrame is then returned. populate_buy_trend function: This function takes a DataFrame and a metadata dictionary as inputs and returns a modified DataFrame. It defines multiple sets of conditions using boolean expressions, each representing a potential buy signal. The conditions check various indicators, such as moving averages (ema), bollinger bands (bb), relative strength index (rsi), and volume, to determine if a buy signal is present. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'buy' column. The modified DataFrame is then returned. populate_sell_trend function: This function takes a DataFrame and a metadata dictionary as inputs and returns a modified DataFrame. It defines two sets of conditions using boolean expressions, representing potential sell signals. The conditions check the price surpassing the upper Bollinger band and the relative strength index (rsi) reaching a certain value. If any of the conditions are satisfied, the corresponding row in the DataFrame is marked with a value of 1 in the 'sell' column. The modified DataFrame is then returned. Overall, the strategy combines various technical indicators to generate buy and sell signals based on specific conditions in the market.
stoploss: -0.99 timeframe: 5m hash(sha256): cdce571d5d490d5bf1a6bfd3bca78d35a52920b024073866f1f186180fb4adf3
Was not able to fetch indicators from Strategyfile.
last change: 2023-04-26 16:58:57