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The BinClucMadSMADevelop strategy is a trading strategy implemented as a class in Python. It inherits from the IStrategy class, indicating that it follows a specific interface for backtesting. The strategy consists of two main methods: populate_indicators and populate_buy_trend.
In the populate_indicators method, the strategy calculates various indicators based on the provided dataframe and metadata.
It uses the informative_1h_indicators and normal_tf_indicators functions to generate additional information at different timeframes.
The resulting indicators are merged into the original dataframe and returned. In the populate_buy_trend method, the strategy defines multiple buy conditions and enables corresponding flags in the dataframe. These conditions are based on comparisons between different columns of the dataframe and certain threshold values. The strategy checks various indicators such as moving averages (ma_buy), Exponential Weighted Oscillator (EWO), Relative Strength Index (rsi), Bollinger Bands (bbdelta, closedelta, lower), Exponential Moving Averages (ema_200, ema_50, ema_50_1h, ema_200_1h), and others. If a particular condition is met, the corresponding flag is set to 1. Overall, the strategy aims to identify potential buy opportunities based on the defined conditions and calculated indicators. It utilizes a combination of technical analysis indicators and specific threshold values to make buying decisions.
In the populate_indicators method, the strategy calculates various indicators based on the provided dataframe and metadata.
It uses the informative_1h_indicators and normal_tf_indicators functions to generate additional information at different timeframes.
The resulting indicators are merged into the original dataframe and returned. In the populate_buy_trend method, the strategy defines multiple buy conditions and enables corresponding flags in the dataframe. These conditions are based on comparisons between different columns of the dataframe and certain threshold values. The strategy checks various indicators such as moving averages (ma_buy), Exponential Weighted Oscillator (EWO), Relative Strength Index (rsi), Bollinger Bands (bbdelta, closedelta, lower), Exponential Moving Averages (ema_200, ema_50, ema_50_1h, ema_200_1h), and others. If a particular condition is met, the corresponding flag is set to 1. Overall, the strategy aims to identify potential buy opportunities based on the defined conditions and calculated indicators. It utilizes a combination of technical analysis indicators and specific threshold values to make buying decisions.
stoploss: -0.228 timeframe: 5m hash(sha256): 5ab2b82f57a2b120450638bae1427416518d882f0273de0a704e729359af7021 indicators: sma_200_1h EWO v9_buy_condition_4_enable ema_200 ema_50 v9_buy_condition_8_enable close sma_5 tail v9_buy_condition_1_enable f"ma_buy_val bb_lowerband mfi bbdelta v6_buy_condition_3_enable volume ma_buy v6_buy_condition_2_enable closedelta date conditions_count open v8_buy_condition_3_enable volume_mean_slow v9_buy_condition_7_enable v9_buy_condition_3_enable v9_buy_condition_6_enable ema_50_1h sma_200 v8_buy_condition_0_enable v9_buy_condition_10_enable mid smaoffset_buy_condition_0_enable v6_b
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last change: 2023-04-26 07:21:46