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The NostalgiaForInfinityNext strategy is a trading strategy implemented as a class that inherits from the IStrategy base class. Here is a brief description of what the strategy does:
populate_indicators method:
Retrieves BTC (Bitcoin) price data for informative timeframes (5 minutes and 1 hour) and performs calculations on the data to generate indicators. Merges the informative BTC data with the main trading data.
Performs additional calculations and merges informative data from other timeframes if specified.
Calculates indicators for the normal timeframe (5 minutes).
Returns the updated dataframe with indicators. populate_buy_trend method: Initializes a list of conditions for potential buy signals. Iterates through the buy protection parameters and adds conditions based on the specified criteria. Applies buy logic conditions based on the index value. Returns the updated dataframe with a 'buy_tag' column indicating potential buy signals. The strategy essentially populates various indicators based on different timeframes and conditions. The populate_indicators method prepares the data by merging informative and resampled timeframes and calculates indicators, while the populate_buy_trend method sets up buy conditions based on specified parameters and indicators. Please note that the provided code snippet is incomplete, and there may be additional methods or functionality within the NostalgiaForInfinityNext class that are not shown.
Performs additional calculations and merges informative data from other timeframes if specified.
Calculates indicators for the normal timeframe (5 minutes).
Returns the updated dataframe with indicators. populate_buy_trend method: Initializes a list of conditions for potential buy signals. Iterates through the buy protection parameters and adds conditions based on the specified criteria. Applies buy logic conditions based on the index value. Returns the updated dataframe with a 'buy_tag' column indicating potential buy signals. The strategy essentially populates various indicators based on different timeframes and conditions. The populate_indicators method prepares the data by merging informative and resampled timeframes and calculates indicators, while the populate_buy_trend method sets up buy conditions based on specified parameters and indicators. Please note that the provided code snippet is incomplete, and there may be additional methods or functionality within the NostalgiaForInfinityNext class that are not shown.
stoploss: -0.99 timeframe: 5m hash(sha256): 9b6c1c4aa477defea1d2222fb7e78803bc79101afe37c32ed1dd24cd704b3e93 indicators: sma_200_1h upper safe_pump_type safe_pump_24_30 leading_senkou_span_b_1h close ema_15 senkou_a sell_pump_36_2 sma_5 sell_pump_24_1_1h safe_pump_period ema_25 ema_200_1h tenkan_sen 39 safe_dump_50 ewo sma200_rising_val r_480_1h safe_pump_24_100 volume rsi_4 sma_200_dec_20 leading_senkou_span_a senkou_a senkou_b safe_pump_24_120 safe_dips_70 sell_pump_36_1_1h ema_20 source safe_pump_48_30 buy_tag oc_pct_change_48 sell_pump_48_1_1h rsi_14 high efi tpct_change_2 safe_dips_30 r_480 sell_pump_48_3 chi
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last change: 2023-08-21 21:18:28