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The BB_RPB_TSL_Tranz strategy is a trading strategy implemented in a backtesting website. Here's a short description of what the strategy does:
The strategy uses various technical indicators to make buying decisions in the market. It starts by populating indicators using different timeframes (1-hour and 15-minute) to gather relevant data.
Then, it identifies buy conditions based on a set of predefined rules.
The buy conditions include checks for various indicators such as rate of change (roc), Bollinger Bands width (bb_width), relative momentum index (rmi), commodity channel index (cci), stochastic relative strength index (srsi_fk), Keltner Channels (kc), exponential moving averages (ema), and others.
Once the buy conditions are met, a buy signal is generated, and the strategy marks the corresponding data points as potential buy opportunities. The specific conditions for generating buy signals involve additional checks, local uptrends, local dips, exponential weighted oscillators (ewo), reverse deadfish pattern, ClucHA pattern, cofi pattern, gumbo pattern, and squeeze momentum (sqzmom). By backtesting the strategy on historical market data, users can evaluate its performance and assess its effectiveness in generating profitable trading signals.
Then, it identifies buy conditions based on a set of predefined rules.
The buy conditions include checks for various indicators such as rate of change (roc), Bollinger Bands width (bb_width), relative momentum index (rmi), commodity channel index (cci), stochastic relative strength index (srsi_fk), Keltner Channels (kc), exponential moving averages (ema), and others.
Once the buy conditions are met, a buy signal is generated, and the strategy marks the corresponding data points as potential buy opportunities. The specific conditions for generating buy signals involve additional checks, local uptrends, local dips, exponential weighted oscillators (ewo), reverse deadfish pattern, ClucHA pattern, cofi pattern, gumbo pattern, and squeeze momentum (sqzmom). By backtesting the strategy on historical market data, users can evaluate its performance and assess its effectiveness in generating profitable trading signals.
stoploss: -0.99 timeframe: 5m hash(sha256): dfed185609c239b2fdc876d2915d08e9fdef2009bc1bcf0edcf4e71095131e34 indicators: upper close low_s volume_mean_12 ema_25 ema_200_1h safe_dump_50 ewo rsi_fast avg_val_20 r_480_1h sma_15_15m volume rsi_4 sma_200_dec_20 xe1 ema_20 source ha_closedelta momdiv_coh bb20_3_low buy_tag trange rsi_14 bb_upperband2 volume_mean_24 high ema_8 r_480 cci bb_lowerband3 rsi_1h xe6 final_ub low_5 close_15m openclosehighlow bb20_2_mid momdiv_col ha_high pm adx ema_12 sma_28 T3Average open_15m ema_slow ema_26 runmode bb_width_1h bb_lowerband2_40 cmf_1h bb_upperband2_40 basic_ub rsi_20 sma_21 m
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last change: 2024-05-02 23:27:23