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The ClucHAnix_BB_RPB_MOD strategy is a trading strategy that involves various technical indicators to make buy decisions in the market. Here's a breakdown of its main components:
Indicators:
Heikin Ashi candles: Calculated using the qtpylib.heikinashi function, these candles smooth out price fluctuations. Exponential Moving Averages (EMA): Three EMAs with periods 8, 14, and 26 are calculated using the ta.EMA function.
Simple Moving Average (SMA): A 15-period SMA is calculated using the ta.SMA function.
Relative Strength Index (RSI): Three RSIs with periods 4, 14, and 20 are calculated using the ta.RSI function.
Commodity Channel Index (CTI): Calculated using the pta.cti function. Stochastic Oscillator: Fast %D and %K values are calculated using the ta.STOCHF function. Average Directional Index (ADX): Calculated using the ta.ADX function. Bollinger Bands: Two sets of Bollinger Bands are calculated using different methods (bollinger_bands and qtpylib.bollinger_bands). Price delta and Bollinger Bands delta: Absolute differences between price values and Bollinger Bands are calculated. Tail: Difference between Heikin Ashi close and low prices. Exponential Moving Average (EMA) crossover: Fast and slow EMAs are calculated using the ta.EMA function. Rate of Change Ratio (ROCR): Calculated using the ta.ROCR function. Elliott Wave Oscillator (EWO): Calculated using the EWO function. Fisher Transform: A transformation of RSI values using the Fisher Transform formula. Informative data: Additional data for the '1h' timeframe is retrieved and merged with the main dataframe. Bitcoin data: Close price data for 'BTC/USDT' pair on '1m' and '1d' timeframes is retrieved and merged with the main dataframe. Zero Lag Exponential Moving Averages (ZEMA): Two ZEMAs with periods 30 and 200 are calculated using the ftt.zema function. Pump Strength: The difference between ZEMA(30) and ZEMA(200) divided by ZEMA(30). Buy Conditions: The strategy defines several conditions for initiating a buy signal. Each condition is associated with a specific tag. The conditions include: BTC safety check: Ensures that the percentage change between 'BTC/USDT' close prices on '1m' and '1d' timeframes meets a specified threshold and the volume is nonzero. Pump safety check: Ensures that the pump strength is below a specified threshold. Lambo1: Checks if the close price is below a factor (lambo1_ema_14_factor) multiplied by EMA(14) and if both RSI(4) and RSI(14) are below specified limits. Lambo2: Similar to Lambo1 but with different factor and limit values. Local Uptrend: Checks if EMA(26) is above EMA(14), the difference between the two EMAs is greater than a percentage of the open price (local_trend_ema_diff), the previous difference is positive, the close price is below bb_lowerband2 multiplied by a factor (local_trend_bb_factor), and the absolute difference between consecutive close prices is greater than a percentage of the close price (local_trend_closedelta). NFI_32: Checks if RSI(20) is lower than the previous RSI(20), RSI(4) is below a specified value, RSI(14) is above a specified value, the close price is below SMA(15) multiplied by a factor (nfi32_sma_factor), and CTI is below a specified limit. EWO_1: Checks if RSI(4) is below a specified value, the close price is below a factor (ewo_low_offset) multiplied by EMA(Buy Candles) and above a specified value (ewo_high), RSI(14) is below a specified value, and the close price is below a factor (ewo_high_offset) multiplied by EMA(Sell Candles). EWO_Low: Similar to EWO_1 but with different RSI(4) and EWO values. COFI: Checks if the open price is below EMA(8) multiplied by a specified value (cofi_ema), if the fast %K crosses above the fast %D, if both fast %K and %D are below specified values (cofi_fastk and cofi_fastd), and if ADX is below a specified value. The strategy populates a 'buy_tag' column in the dataframe to indicate the conditions that are met for each buy signal. Please note that the provided code snippet appears to be a Python implementation of the strategy using various libraries and functions.
Simple Moving Average (SMA): A 15-period SMA is calculated using the ta.SMA function.
Relative Strength Index (RSI): Three RSIs with periods 4, 14, and 20 are calculated using the ta.RSI function.
Commodity Channel Index (CTI): Calculated using the pta.cti function. Stochastic Oscillator: Fast %D and %K values are calculated using the ta.STOCHF function. Average Directional Index (ADX): Calculated using the ta.ADX function. Bollinger Bands: Two sets of Bollinger Bands are calculated using different methods (bollinger_bands and qtpylib.bollinger_bands). Price delta and Bollinger Bands delta: Absolute differences between price values and Bollinger Bands are calculated. Tail: Difference between Heikin Ashi close and low prices. Exponential Moving Average (EMA) crossover: Fast and slow EMAs are calculated using the ta.EMA function. Rate of Change Ratio (ROCR): Calculated using the ta.ROCR function. Elliott Wave Oscillator (EWO): Calculated using the EWO function. Fisher Transform: A transformation of RSI values using the Fisher Transform formula. Informative data: Additional data for the '1h' timeframe is retrieved and merged with the main dataframe. Bitcoin data: Close price data for 'BTC/USDT' pair on '1m' and '1d' timeframes is retrieved and merged with the main dataframe. Zero Lag Exponential Moving Averages (ZEMA): Two ZEMAs with periods 30 and 200 are calculated using the ftt.zema function. Pump Strength: The difference between ZEMA(30) and ZEMA(200) divided by ZEMA(30). Buy Conditions: The strategy defines several conditions for initiating a buy signal. Each condition is associated with a specific tag. The conditions include: BTC safety check: Ensures that the percentage change between 'BTC/USDT' close prices on '1m' and '1d' timeframes meets a specified threshold and the volume is nonzero. Pump safety check: Ensures that the pump strength is below a specified threshold. Lambo1: Checks if the close price is below a factor (lambo1_ema_14_factor) multiplied by EMA(14) and if both RSI(4) and RSI(14) are below specified limits. Lambo2: Similar to Lambo1 but with different factor and limit values. Local Uptrend: Checks if EMA(26) is above EMA(14), the difference between the two EMAs is greater than a percentage of the open price (local_trend_ema_diff), the previous difference is positive, the close price is below bb_lowerband2 multiplied by a factor (local_trend_bb_factor), and the absolute difference between consecutive close prices is greater than a percentage of the close price (local_trend_closedelta). NFI_32: Checks if RSI(20) is lower than the previous RSI(20), RSI(4) is below a specified value, RSI(14) is above a specified value, the close price is below SMA(15) multiplied by a factor (nfi32_sma_factor), and CTI is below a specified limit. EWO_1: Checks if RSI(4) is below a specified value, the close price is below a factor (ewo_low_offset) multiplied by EMA(Buy Candles) and above a specified value (ewo_high), RSI(14) is below a specified value, and the close price is below a factor (ewo_high_offset) multiplied by EMA(Sell Candles). EWO_Low: Similar to EWO_1 but with different RSI(4) and EWO values. COFI: Checks if the open price is below EMA(8) multiplied by a specified value (cofi_ema), if the fast %K crosses above the fast %D, if both fast %K and %D are below specified values (cofi_fastk and cofi_fastd), and if ADX is below a specified value. The strategy populates a 'buy_tag' column in the dataframe to indicate the conditions that are met for each buy signal. Please note that the provided code snippet appears to be a Python implementation of the strategy using various libraries and functions.
stoploss: -0.99 timeframe: 1m hash(sha256): 3200f5489d4d5ecac08c01ebcf6f832d430b5129393eb82331f60572aaf4c1ff 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 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 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_sma_factor cofi_
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last change: 2022-07-02 19:54:08