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The BigZ04_TSL4 strategy is a trading strategy implemented as a class that inherits from the IStrategy interface. It consists of several methods that perform different tasks. The populate_indicators method takes a DataFrame of trading data and a metadata dictionary as input.
It uses the informative_1h_indicators function to calculate indicators for a 1-hour timeframe and merges the resulting indicators with the original DataFrame using the merge_informative_pair function.
Then, it applies additional indicators using the normal_tf_indicators function.
The method returns the modified DataFrame with all the indicators. The populate_buy_trend method also takes a DataFrame and a metadata dictionary as input. It defines a list of conditions that must be met for a buy signal to be generated. Each condition is expressed as a logical expression involving different columns of the DataFrame. The conditions include checks on the closing price, exponential moving averages (EMA), Bollinger Bands (BB), relative strength index (RSI), volume, and open/close prices. If any of the conditions are met, a buy signal is generated. The method returns the DataFrame with the buy signals. Overall, the strategy aims to identify buying opportunities based on various technical indicators and market conditions.
It uses the informative_1h_indicators function to calculate indicators for a 1-hour timeframe and merges the resulting indicators with the original DataFrame using the merge_informative_pair function.
Then, it applies additional indicators using the normal_tf_indicators function.
The method returns the modified DataFrame with all the indicators. The populate_buy_trend method also takes a DataFrame and a metadata dictionary as input. It defines a list of conditions that must be met for a buy signal to be generated. Each condition is expressed as a logical expression involving different columns of the DataFrame. The conditions include checks on the closing price, exponential moving averages (EMA), Bollinger Bands (BB), relative strength index (RSI), volume, and open/close prices. If any of the conditions are met, a buy signal is generated. The method returns the DataFrame with the buy signals. Overall, the strategy aims to identify buying opportunities based on various technical indicators and market conditions.
stoploss: -0.99 timeframe: 5m hash(sha256): 121f6bb4535cefaae82db0a059fd1daa896a8a523bcfaabf4f1ef7b269b01edf indicators: upper ema_200 ema_50 close sma_5 bb_lowerband ema_200_1h ma_sell_val volume open volume_mean_slow mid macd rsi_1h bb_lowerband_1h hist atr lower ema_12 signal bb_middleband rsi bb_upperband ema_26 low close_1h
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last change: 2022-07-10 22:12:24