Strategy: BBMod_1
Downloaded: 20220303
Stoploss: -0.99

Strategy failed backtesting!
Reason: Duplicate of BBMod_0

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The "BBMod" strategy is a trading strategy that uses various indicators to identify buying and selling opportunities in the market. Here is a summary of what the strategy does: populate_indicators: This function populates the indicators used in the strategy. It merges informative data from the 1-hour timeframe with the current timeframe data and computes other indicators.

populate_buy_trend: This function defines the conditions for buying based on different indicator combinations.

It checks for conditions related to local uptrends, local dips, EWO (Elliott Wave Oscillator), Clucha, NFI (Next Financial Indicator), NFIX (Next Financial Indicator Extended), and VWAP (Volume Weighted Average Price).

If any of the conditions are met, the 'buy' signal is generated. populate_sell_trend: This function generates a 'sell' signal unconditionally. It marks all data points with a 'sell' signal. The "BBMod1DCA" class inherits from the "BBMod" class and adds additional functionality specific to a 1DCA (1-Day Close Average) variation of the strategy. Overall, the strategy combines multiple indicators to identify potential buying opportunities and generates a 'buy' signal when the specified conditions are met. It also generates a 'sell' signal unconditionally.

stoploss: -0.99
timeframe: 5m
hash(sha256): 5f4d8dd734ce6cb5954dbdfc7e0d15dd3961b61852bf03a379dda1532ba3b427
rocr_1h bb_upperband2_40 upper EWO ha_low
ema_200 ema_50 ema_13 close high_offset_2
ema_49 tail position_adjustment_enable crsi ema_200_1h
vwap_high sma_21 rsi_fast bb_middleband2 volume
closedelta rsi_84 rocr ema_20 open
ha_closedelta ema_fast vwap_low bb_middleband2_40 sma_15
ha_open bb_upperband2 fisher high rsi_112
tcp_percent_4 mid bb_delta_cluc stake_amount ema_24
ema_8 bb_width ema_16 ha_close sma_75
vwap cti sma_9 ema_100 ha_high
lower roc rsi_slow sma_28 sma_30
ema_12 rsi ema_slow ema_4

Similar Strategies: (based on used indicators)

Strategy: BBMod_0, Similarity Score: 98.33%
Strategy: BBMod_2, Similarity Score: 83.33%

last change: 2022-07-02 19:54:08