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The BigZ0407HO 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 trading strategies. The strategy consists of two main methods: populate_indicators and populate_buy_trend.
The populate_indicators method takes a DataFrame and a metadata dictionary as input and returns a modified DataFrame.
It calculates and adds various indicators to the DataFrame using the informative_1h_indicators and normal_tf_indicators functions.
These indicators are used for making trading decisions. The populate_buy_trend method takes the same DataFrame and metadata as input and also returns a modified DataFrame. It defines multiple conditions that determine when to enter a buy trade. Each condition is represented as a logical expression using DataFrame columns and various parameters. These conditions check indicators, moving averages, volume, and other factors to identify favorable buying opportunities. If any of the conditions are met, a buy signal is generated. The strategy is designed to backtest and evaluate different combinations of conditions and indicators to determine their effectiveness in generating profitable trades. It provides a systematic approach to trading decision-making based on predefined rules and indicators.
The populate_indicators method takes a DataFrame and a metadata dictionary as input and returns a modified DataFrame.
It calculates and adds various indicators to the DataFrame using the informative_1h_indicators and normal_tf_indicators functions.
These indicators are used for making trading decisions. The populate_buy_trend method takes the same DataFrame and metadata as input and also returns a modified DataFrame. It defines multiple conditions that determine when to enter a buy trade. Each condition is represented as a logical expression using DataFrame columns and various parameters. These conditions check indicators, moving averages, volume, and other factors to identify favorable buying opportunities. If any of the conditions are met, a buy signal is generated. The strategy is designed to backtest and evaluate different combinations of conditions and indicators to determine their effectiveness in generating profitable trades. It provides a systematic approach to trading decision-making based on predefined rules and indicators.
stoploss: -0.99 timeframe: 5m hash(sha256): d5d4fc34118e94421e57b0cba6c59c54a5bb24bdeb3512a51a901e13b2bd87d4 indicators: sell_pump_36_3_1h upper close ema_15 sell_pump_36_2 sma_5 sell_pump_24_1_1h bb_lowerband ema_200_1h ewo volume sma_200_dec_20 sell_pump_36_1_1h ema_20 oc_pct_change_48 sell_pump_48_1_1h high tpct_change_2 sell_pump_48_3 rsi_1h bb20_2_mid hist ema_12 tpct_change_12 sell_pump_48_2 ema_26 sell_pump_24_1 chop oc_pct_change_36 bb20_2_upp_1h closedelta bb20_2_low volume_mean_4 tpct_change_0 bb_lowerband_1h sell_pump_48_2_1h lower signal rsi sell_pump_24_3 sell_pump_36_2_1h hl_pct_change_36 ema_50 tail
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last change: 2023-06-29 01:40:23