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Strategy: ClucHAnix_BB_RPB
Downloaded: 20220113
Stoploss: -0.99
1mSpotv2UnbiasedLink


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Average Overall
BuysAvgprofTotProfWin%DD%Time
280-0.02-2.7172.512.35195.75
SharpeSortinoCalmar
-0.63-0.242.29
Prof.FactorExpectancyCagr
0.4700
Trades/DayRejected Signals
10.54104
Ninja Score: 52
The ClucHAnix_BB_RPB strategy is a backtesting trading strategy that makes use of various technical indicators to generate buy signals. Here is a short description of what the strategy does: The strategy starts by populating a set of indicators based on the input dataframe. It calculates Heikin-Ashi candles, exponential moving averages (EMA) of different time periods (8, 14, and 26), simple moving average (SMA) with a time period of 15, relative strength index (RSI) for different time periods (4, 14, and 20), Commodity Channel Index (CTI) with a length of 20, stochastic fast indicators, average directional index (ADX), Bollinger Bands with a window size of 40 and 2 standard deviations, and other derived indicators.

Next, the strategy populates the buy trend by evaluating various conditions.

It checks if the percentage change between the 1-day and 1-minute BTC/USDT close prices is above a specified threshold and ensures that the volume is not zero.

It also checks if the "pump strength" (the difference between two exponential moving averages) is below a specified threshold. The strategy defines several conditions for different buy tags. It checks for "lambo1" and "lambo2" conditions based on the close price, RSI values, and exponential moving averages. It also checks for a local uptrend condition based on the relationship between exponential moving averages, Bollinger Bands, close price delta, and other factors. Another condition is based on a negative flip index (NFI) and checks for RSI values, close price, simple moving average, and CTI. The strategy also includes conditions for EWO (Elliott Wave Oscillator) values, close price, and exponential moving averages. Finally, the strategy assigns buy tags to the dataframe based on the conditions met and appends the conditions to a list. Other conditions, such as COFI (Crossover of Fast Stochastic K and D), are truncated in the provided code snippet. Overall, the strategy combines various indicators and conditions to generate buy signals based on specific market patterns and price movements.

rade_exit trade.sell_reason = sell_reason + "_" + trade.buy_tag ^^^^^^^^^^^^^^^^^ AttributeError: property 'sell_reason' of 'LocalTrade' object has no setter
stoploss: -0.99
timeframe: 1m
hash(sha256): ada277ad04087ec7a2ec6c03bb785a50e0a05c4e3a639c60626bd1850e18ca4c
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 ha_open
sma_15 nfi32_sma_factor cofi_fastd low

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last change: 2024-04-02 03:37:27