Not Enough Data to display!
Average Overall
| Not Enough Data! / Avg statistics not populated yet. |
|---|
The ClucHAnix_5M_E0V1E strategy is a backtesting strategy that makes use of various indicators to generate buy and sell signals. Here is a description of its key components:
populate_indicators: This function calculates and adds several indicators to the input dataframe, including Heikin-Ashi candles, Bollinger Bands, exponential moving averages (EMA), rate of change ratio (ROCR), relative strength index (RSI), Fisher transform, percentage change, and normalized percentage change. It also merges informative data from a higher timeframe.
populate_buy_trend: This function populates the buy signals in the dataframe based on predefined buy parameters.
It checks conditions such as the rate of change ratio, Bollinger Bands, candlestick patterns, and moving averages to determine if a buy signal should be generated.
populate_sell_trend: This function populates the sell signals in the dataframe based on predefined sell parameters. It checks conditions such as the Fisher transform, candlestick patterns, moving averages, and volume to determine if a sell signal should be generated. The ClucHAnix_5M_E0V1E_DYNAMIC_TB class extends the ClucHAnix_5M_E0V1E class and adds additional functionality related to trailing buy orders. It includes methods for trailing buy order management, confirmation of trade entry, and updating trailing buy prices based on market movements. Overall, the strategy utilizes a combination of technical indicators and predefined parameters to generate buy and sell signals for backtesting trading strategies.
populate_buy_trend: This function populates the buy signals in the dataframe based on predefined buy parameters.
It checks conditions such as the rate of change ratio, Bollinger Bands, candlestick patterns, and moving averages to determine if a buy signal should be generated.
populate_sell_trend: This function populates the sell signals in the dataframe based on predefined sell parameters. It checks conditions such as the Fisher transform, candlestick patterns, moving averages, and volume to determine if a sell signal should be generated. The ClucHAnix_5M_E0V1E_DYNAMIC_TB class extends the ClucHAnix_5M_E0V1E class and adds additional functionality related to trailing buy orders. It includes methods for trailing buy order management, confirmation of trade entry, and updating trailing buy prices based on market movements. Overall, the strategy utilizes a combination of technical indicators and predefined parameters to generate buy and sell signals for backtesting trading strategies.
startup_candle_count : 168 ema_slow: 0.003% fisher: -0.008%
Unable to parse Traceback (Logfile Exceeded Limit)
stoploss: -0.99 timeframe: 5m hash(sha256): a3124af99b848a700e07e929362231f0cbf2cfdf458cdcb442fa75a0835c779c indicators: rocr_1h closedeltaclose roi_p6 closebblower ha_low sellbbmiddleclose close roi_t3 tail bb_lowerband bbdelta volume bbdeltaclose roi_p1 roi_t4 roi_p2 roi_p3 perc closedelta roi_t5 rocr open ema_fast volume_mean_slow buy_tag ha_open sellfisher fisher high mid bbdeltatail ha_close roi_p4 buy ha_high lower rocr1h bb_middleband rsi offset roi_p5 ema_slow runmode roi_t2 low avg3_perc roi_t6 norm_perc
Similar Strategies: (based on used indicators)
Strategy: Discord_ClucHAnix_5M_E0V1E, Similarity Score: 97.96%
Strategy: CE01, Similarity Score: 83.67%
Strategy: ClucHAnixE01VEOffsets, Similarity Score: 83.67%
Strategy: ClucHAnix_932, Similarity Score: 83.67%
Strategy: Discord_1_ClucHAnix, Similarity Score: 83.67%
Strategy: BC_Redmoon, Similarity Score: 77.55%
Strategy: TrailingBuy_ClucHAnix_5m_E0V1E_by_TraNz, Similarity Score: 77.55%
Strategy: TrailingBuy_ClucHAnix_5m_E0V1E_by_TraNz201, Similarity Score: 77.55%
last change: 2024-08-02 09:41:22