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The BigZ03 strategy is a trading strategy implemented as a class that inherits from the IStrategy interface. It consists of several methods that define its behavior. The populate_indicators method is responsible for calculating and adding various indicators to the input dataframe.
It calls the informative_1h_indicators method to calculate indicators based on 1-hour data and merges the results into the main dataframe.
Then, it applies additional indicators using the normal_tf_indicators method and returns the modified dataframe.
The populate_buy_trend method determines the buying conditions for the strategy. It checks various conditions using logical operators and column comparisons within the dataframe. The conditions involve comparisons with moving averages (ema_200, ema_200_1h), Bollinger Bands (bb_lowerband, bb_middleband, bb_upperband), relative strength index (rsi, rsi_1h), volume, open, close, and other variables. If any of the conditions are met, a buying signal is generated for the corresponding data point in the dataframe. Overall, the BigZ03 strategy aims to identify potential buying opportunities based on specific technical indicators and conditions in the market. It uses a combination of moving averages, Bollinger Bands, volume analysis, and other criteria to determine when to enter a trade.
It calls the informative_1h_indicators method to calculate indicators based on 1-hour data and merges the results into the main dataframe.
Then, it applies additional indicators using the normal_tf_indicators method and returns the modified dataframe.
The populate_buy_trend method determines the buying conditions for the strategy. It checks various conditions using logical operators and column comparisons within the dataframe. The conditions involve comparisons with moving averages (ema_200, ema_200_1h), Bollinger Bands (bb_lowerband, bb_middleband, bb_upperband), relative strength index (rsi, rsi_1h), volume, open, close, and other variables. If any of the conditions are met, a buying signal is generated for the corresponding data point in the dataframe. Overall, the BigZ03 strategy aims to identify potential buying opportunities based on specific technical indicators and conditions in the market. It uses a combination of moving averages, Bollinger Bands, volume analysis, and other criteria to determine when to enter a trade.
startup_candle_count : 200 ema_50_1h: -0.001% macd: -0.001% signal: -0.002% hist: 0.002%
stoploss: -0.99 timeframe: 5m hash(sha256): cf4f30a01aa616728509d430d0b28a111d9e69de4a1c4cd0e2a00187e04057b9 indicators: upper ema_200 ema_50 close sma_5 bb_lowerband ema_200_1h volume open volume_mean_slow high mid macd rsi_1h hist lower ema_12 signal bb_middleband rsi bb_upperband ema_26 low
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last change: 2023-07-01 19:43:22