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The "ClucHAnix_BB_RPB_MOD" strategy is designed to backtest trading strategies. Here is a short description of what the strategy does:
It populates various indicators for the given dataframe, including Heikin-Ashi candles, exponential moving averages (EMA), simple moving average (SMA), relative strength index (RSI), Commodity Channel Index (CTI), Stochastic Fast, Average Directional Index (ADX), Bollinger Bands, and others. It merges informative data for an additional timeframe, such as 1-hour data, and calculates additional indicators for the merged dataframe.
It retrieves BTC/USDT price data for 1-minute and 1-day timeframes and merges it with the main dataframe.
It calculates the pump strength indicator based on exponential moving averages and uses it in subsequent conditions.
It populates the buy trend based on various conditions: BTC safety: Checks if the percentage change between 1-day and 1-minute BTC prices is above a certain threshold and ensures that the volume is not zero. Pump safety: Checks if the pump strength indicator is below a specified threshold. Lambo1: Checks if the close price is below a certain factor of the EMA-14, and RSI-4 and RSI-14 are below specified limits. Lambo2: Similar to Lambo1, but with different parameter values. Local uptrend: Checks if the EMA-26 is greater than EMA-14, the difference between the EMAs is significant, the close price is below the lower Bollinger Band, and other conditions related to price movements are met. NFI_32: Checks for specific conditions related to RSI, SMA, and CTI. EWO_1: Checks for conditions related to RSI, close price, EWO indicator, and moving averages. EWO_low: Checks for conditions similar to EWO_1 but with different EWO indicator threshold. COFI: Checks for conditions related to opening price, EMA-8, Stochastic Fast, and ADX indicators. It assigns a buy tag to the dataframe based on the conditions that are met. The strategy aims to identify potential buying opportunities based on the specified conditions and indicators.
It retrieves BTC/USDT price data for 1-minute and 1-day timeframes and merges it with the main dataframe.
It calculates the pump strength indicator based on exponential moving averages and uses it in subsequent conditions.
It populates the buy trend based on various conditions: BTC safety: Checks if the percentage change between 1-day and 1-minute BTC prices is above a certain threshold and ensures that the volume is not zero. Pump safety: Checks if the pump strength indicator is below a specified threshold. Lambo1: Checks if the close price is below a certain factor of the EMA-14, and RSI-4 and RSI-14 are below specified limits. Lambo2: Similar to Lambo1, but with different parameter values. Local uptrend: Checks if the EMA-26 is greater than EMA-14, the difference between the EMAs is significant, the close price is below the lower Bollinger Band, and other conditions related to price movements are met. NFI_32: Checks for specific conditions related to RSI, SMA, and CTI. EWO_1: Checks for conditions related to RSI, close price, EWO indicator, and moving averages. EWO_low: Checks for conditions similar to EWO_1 but with different EWO indicator threshold. COFI: Checks for conditions related to opening price, EMA-8, Stochastic Fast, and ADX indicators. It assigns a buy tag to the dataframe based on the conditions that are met. The strategy aims to identify potential buying opportunities based on the specified conditions and indicators.
stoploss: -0.99 timeframe: 1m hash(sha256): 43899d1cab442ebf2c42bc6ee2438b93696e2e099057d81ba6a6b08fc06de2a5 indicators: upper local_trend_bb_factor lambo1_ema_14_factor close cofi_ema bb_lowerband lambo1_rsi_4_limit lambo2_rsi_4_limit volume rsi_4 date close ha_closedelta buy_tag clucha_bbdelta_close rsi_14 bb_upperband2 high ewo_low_offset ema_8 ewo_low_enabled antipump_threshold pump_strength ha_high cofi_enabled adx ema_slow ema_26 runmode ewo_candles_buy local_trend_enabled ewo_high ewo_low rsi_20 bbdelta bb_middleband2 cofi_fastk cofi_ewo_high nfi32_cti_limit closedelta zema_30 ema_fast ha_open sma_15 nfi32_
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last change: 2022-07-02 19:54:08