The BB_RPB_TSLmeneguzzo strategy is a backtesting strategy that evaluates trading conditions based on various indicators and generates buy signals. Here is a breakdown of the important parts of the strategy:
populate_indicators: This method populates the indicators used in the strategy. It takes a DataFrame and metadata as inputs and returns the updated DataFrame.
populate_buy_trend: This method identifies the conditions for generating buy signals.
It creates a column called 'buy_tag' in the DataFrame and sets it to an empty string.
It then defines various conditions using different indicators and assigns boolean values to each condition. Some of the important conditions include: is_dip: Determines if the price is in a dip based on RMI, CCI, and SRSI indicators. is_sqzOff: Checks if the Bollinger Bands are in a squeeze-off state. is_break: Identifies a breakout condition based on Bollinger Bands, delta, and width. is_local_uptrend: Detects a local uptrend using EMA indicators. is_ewo: Evaluates EWO (Elliott Wave Oscillator) and RSI indicators. is_ewo_2: Considers EWO, RSI, and EMA indicators in a different configuration. is_r_deadfish: Checks for a reverse deadfish pattern using EMA, Bollinger Bands, and volume. is_clucHA: Identifies a specific pattern based on ROCR, Bollinger Bands, and HA (Heikin-Ashi) indicators. is_gumbo: Considers EWO, Bollinger Bands, T3 indicator, CTI, and RSI for pattern detection. is_sqzmom: Evaluates squeezeMomentum conditions based on Bollinger Bands, linear regression, EMA, EWO, and RSI. is_nfi_13: Considers various indicators for a specific pattern (NFI 13). is_nfi_32: Checks for a specific pattern (NFI 32) based on RSI, SMA, CTI, and close price. is_nfi_33: Identifies a pattern (NFI 33) based on close price, EWO, CTI, RSI, R, and volume. is_nfix_5: Considers EMA, close price, EWO, CTI, R, and SMA for a specific pattern (NFIX 5). is_nfix_49: Evaluates EMA and a specific pattern (NFIX 49) based on EMA and R. These conditions are evaluated for each data point in the DataFrame, and if any condition is met, the 'buy_tag' column is updated accordingly. Overall, the BB_RPB_TSLmeneguzzo strategy combines multiple indicators and pattern detection techniques to generate buy signals based on specific market conditions.
populate_buy_trend: This method identifies the conditions for generating buy signals.
It creates a column called 'buy_tag' in the DataFrame and sets it to an empty string.
It then defines various conditions using different indicators and assigns boolean values to each condition. Some of the important conditions include: is_dip: Determines if the price is in a dip based on RMI, CCI, and SRSI indicators. is_sqzOff: Checks if the Bollinger Bands are in a squeeze-off state. is_break: Identifies a breakout condition based on Bollinger Bands, delta, and width. is_local_uptrend: Detects a local uptrend using EMA indicators. is_ewo: Evaluates EWO (Elliott Wave Oscillator) and RSI indicators. is_ewo_2: Considers EWO, RSI, and EMA indicators in a different configuration. is_r_deadfish: Checks for a reverse deadfish pattern using EMA, Bollinger Bands, and volume. is_clucHA: Identifies a specific pattern based on ROCR, Bollinger Bands, and HA (Heikin-Ashi) indicators. is_gumbo: Considers EWO, Bollinger Bands, T3 indicator, CTI, and RSI for pattern detection. is_sqzmom: Evaluates squeezeMomentum conditions based on Bollinger Bands, linear regression, EMA, EWO, and RSI. is_nfi_13: Considers various indicators for a specific pattern (NFI 13). is_nfi_32: Checks for a specific pattern (NFI 32) based on RSI, SMA, CTI, and close price. is_nfi_33: Identifies a pattern (NFI 33) based on close price, EWO, CTI, RSI, R, and volume. is_nfix_5: Considers EMA, close price, EWO, CTI, R, and SMA for a specific pattern (NFIX 5). is_nfix_49: Evaluates EMA and a specific pattern (NFIX 49) based on EMA and R. These conditions are evaluated for each data point in the DataFrame, and if any condition is met, the 'buy_tag' column is updated accordingly. Overall, the BB_RPB_TSLmeneguzzo strategy combines multiple indicators and pattern detection techniques to generate buy signals based on specific market conditions.
startup_candle_count : 200 ema_50_1h: -0.001% ema_100_1h: -0.011% ema_100: -0.026% rsi_slow: 0.002%
stoploss: -0.99 timeframe: 5m hash(sha256): 4613378ffbc32428be2e8940582923648746376f31670329ce6349871ecdb4aa indicators: upper close volume_mean_12 ema_200_1h safe_dump_50 avg_val_20 rsi_fast r_480_1h volume xe1 ema_20 source ha_closedelta momdiv_coh trange bb_upperband2 volume_mean_24 high ema_8 r_480 cci bb_lowerband3 rsi_1h xe6 final_ub low_5 momdiv_col ha_high pm adx ema_12 sma_28 T3Average ema_slow ema_26 bb_width_1h bb_lowerband2_40 cmf_1h bb_upperband2_40 basic_ub sma_21 momdiv_buy bb_middleband2 closedelta sma_15 ha_open volume_mean_4 avg_close_20 cmf rmi_length_val kc_lowerband_20_2 lower roc T3 r_32 rsi
Similar Strategies: (based on used indicators)
Strategy: BB_RPB_TSL, Similarity Score: 96.55%
Strategy: BB_RPB_TSL_221, Similarity Score: 96.55%
Strategy: BB_RPB_TSL_3, Similarity Score: 96.55%
Strategy: BB_RPB_TSL_8, Similarity Score: 96.55%
Strategy: BB_RPB_TSLmeneguzzo, Similarity Score: 96.55%
Strategy: BB_RPB_TSLmeneguzzo_3, Similarity Score: 96.55%
Strategy: BB_RPB_TSLmeneguzzo_3_2, Similarity Score: 96.55%
Strategy: Discord_1_BB_RPB_TSL, Similarity Score: 96.55%
Strategy: Discord_BB_RPB_TSL, Similarity Score: 96.55%
Strategy: HakimYiech, Similarity Score: 96.55%
Strategy: BB_RPB_TSL_140, Similarity Score: 93.1%
Strategy: BRTMinus, Similarity Score: 93.1%
Strategy: BB_RPB_TSL_4, Similarity Score: 91.38%
Strategy: meneguzzo_v3, Similarity Score: 91.38%
Strategy: meneguzzo_v4_dca, Similarity Score: 91.38%
Strategy: BRTM, Similarity Score: 89.66%
Strategy: BBMod1, Similarity Score: 86.21%
Strategy: BBMod1_2, Similarity Score: 86.21%
Strategy: BBMod1_3, Similarity Score: 86.21%
Strategy: BB_RPB_TSL_600, Similarity Score: 86.21%
Strategy: BB_RPB_TSLX, Similarity Score: 84.48%
Strategy: BB_RPB_TSL_v104, Similarity Score: 84.48%
Strategy: Discord_1_BB_RPB_TSL_BI, Similarity Score: 84.48%
Strategy: gus_delta, Similarity Score: 84.48%
Strategy: BBMod, Similarity Score: 82.76%
Strategy: BBMod1_0, Similarity Score: 82.76%
Strategy: BBMod_6, Similarity Score: 82.76%
Strategy: BB_RPB, Similarity Score: 81.03%
Strategy: BB_RPB_TSL_Tranz203, Similarity Score: 81.03%
Strategy: BB_RPB_TSL_BI, Similarity Score: 77.59%
Strategy: BB_RPB_TSL_BIV1, Similarity Score: 77.59%
Strategy: BB_RPB_TSL_BI_2, Similarity Score: 77.59%
Strategy: BB_RPB_TSL_BI_3, Similarity Score: 77.59%
Strategy: BB_RPB_TSL_BI_v4_EWO2_v3, Similarity Score: 77.59%
Strategy: BB_RPB_TSL_BI_v4_EWO2_v3_0, Similarity Score: 77.59%
Strategy: BRB, Similarity Score: 77.59%
last change: 2024-05-02 12:16:23