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The NASOSv5 strategy is a trading strategy implemented as a class in Python. It has two main functions: populate_indicators and populate_buy_trend, as well as an optional function populate_sell_trend. In the populate_indicators function, the strategy calculates various indicators based on the provided dataframe and metadata.
It merges informative pair data using the merge_informative_pair function and returns the updated dataframe.
The populate_buy_trend function is responsible for determining the buy signals based on specific conditions.
It applies several conditions to identify potential buying opportunities. These conditions include checks on various indicators such as RSI (Relative Strength Index), moving averages, EWO (Elliott Wave Oscillator), and volume. If the conditions are met, the function sets the 'buy' column in the dataframe to 1 and assigns a corresponding 'buy_tag' value. The populate_sell_trend function, if implemented, determines the sell signals based on certain conditions. It includes checks on indicators such as SMA (Simple Moving Average), HMA (Hull Moving Average), RSI, and volume. If the conditions are satisfied, the function sets the 'sell' column in the dataframe to 1. Additionally, there is a subclass called NASOSv5_antipump that inherits from NASOSv5 and overrides the populate_buy_trend and populate_sell_trend functions. This subclass introduces additional conditions specific to anti-pump trading. Overall, the NASOSv5 strategy aims to generate buy and sell signals based on a combination of technical indicators and predefined conditions.
It merges informative pair data using the merge_informative_pair function and returns the updated dataframe.
The populate_buy_trend function is responsible for determining the buy signals based on specific conditions.
It applies several conditions to identify potential buying opportunities. These conditions include checks on various indicators such as RSI (Relative Strength Index), moving averages, EWO (Elliott Wave Oscillator), and volume. If the conditions are met, the function sets the 'buy' column in the dataframe to 1 and assigns a corresponding 'buy_tag' value. The populate_sell_trend function, if implemented, determines the sell signals based on certain conditions. It includes checks on indicators such as SMA (Simple Moving Average), HMA (Hull Moving Average), RSI, and volume. If the conditions are satisfied, the function sets the 'sell' column in the dataframe to 1. Additionally, there is a subclass called NASOSv5_antipump that inherits from NASOSv5 and overrides the populate_buy_trend and populate_sell_trend functions. This subclass introduces additional conditions specific to anti-pump trading. Overall, the NASOSv5 strategy aims to generate buy and sell signals based on a combination of technical indicators and predefined conditions.
stoploss: -0.15 timeframe: 5m hash(sha256): 836e9fb3db5055bdc7dc5edf524986d111be2b9091f14f91c43fab9d42f87e3b indicators: rsi_buy EWO ema_200 ewo_high ema_50 ewo_low high_offset_2 close ewo_high_2 sell_signal profit_threshold rsi_fast ma_sell_val ma_buy_val volume low_offset retries high_offset low_offset_2 base_nb_candles_buy high rsi_fast_buy ___retries base_nb_candles_sell hma_50 buy buy_tag sma_9 ema_100 pump_strength close_15m lookback_candles max_slippage rsi_slow rsi low
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last change: 2022-07-26 19:30:21