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The NostalgiaForInfinityV4HO strategy is a trading strategy implemented as a class in Python. It is designed to be used for backtesting on a trading platform or website. The strategy consists of two main functions: populate_indicators() and populate_buy_trend().
In the populate_indicators() function, various indicators are calculated and populated for the given input dataframe and metadata.
These indicators include informative_1h indicators obtained from the informative_1h_indicators() function, as well as normal time frame indicators obtained from the normal_tf_indicators() function.
The resulting dataframe is returned. The populate_buy_trend() function is responsible for populating the buy conditions or signals for the strategy. It defines multiple conditions using logical operations and comparisons on different columns of the input dataframe. These conditions represent different criteria that need to be met for a buy signal to be generated. Some of the important conditions include checks on moving averages (EMA and SMA), relative strength index (RSI), money flow index (MFI), volume, and various price levels. Each condition is appended to the conditions list. Overall, the strategy aims to identify potential buying opportunities based on a combination of technical indicators and market conditions. The specific conditions and criteria used in the strategy may vary depending on the parameters and values set by the user.
In the populate_indicators() function, various indicators are calculated and populated for the given input dataframe and metadata.
These indicators include informative_1h indicators obtained from the informative_1h_indicators() function, as well as normal time frame indicators obtained from the normal_tf_indicators() function.
The resulting dataframe is returned. The populate_buy_trend() function is responsible for populating the buy conditions or signals for the strategy. It defines multiple conditions using logical operations and comparisons on different columns of the input dataframe. These conditions represent different criteria that need to be met for a buy signal to be generated. Some of the important conditions include checks on moving averages (EMA and SMA), relative strength index (RSI), money flow index (MFI), volume, and various price levels. Each condition is appended to the conditions list. Overall, the strategy aims to identify potential buying opportunities based on a combination of technical indicators and market conditions. The specific conditions and criteria used in the strategy may vary depending on the parameters and values set by the user.
startup_candle_count : 400 ema_100_1h: 0.001% ema_200_1h: 0.078% ewo: 0.086%
Unable to parse Traceback (Logfile Exceeded Limit)
stoploss: -1 timeframe: 5m hash(sha256): 60aa09daffcd6b8b50b7a796ac7fc5ae0487c851cef3c72bffbf4d0c3f5bab2d indicators: sma_200_1h upper ema_200 ema_50 safe_dips jaw close safe_pump_36 ema_15 tail sma_5 safe_pump_36_strict smma_jaw bb_lowerband safe_pump_24_strict mfi safe_pump_48_strict ema_200_1h safe_pump_36_strict_1h bbdelta ewo safe_pump_24 volume ema_100_1h closedelta ema_20 safe_pump_48_1h open safe_pump_24_1h safe_dips_strict volume_mean_30 ema_50_1h bb_upperband_1h sma_200 safe_pump_36_1h volume_mean_4 mid teeth safe_pump_48 rsi_1h ema_100 smma_teeth lower ema_12 sma_30 bb_middleband rsi sma_200_dec bb_u
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last change: 2024-08-02 08:34:17