The ElliotV5 strategy is a backtesting strategy that utilizes various technical indicators to generate buy and sell signals for trading. Here is a short description of what the strategy does:
The strategy starts by populating indicators such as ADX, Plus Directional Movement (PLUS_DM), Plus Directional Indicator (PLUS_DI), Minus Directional Movement (MINUS_DM), Minus Directional Indicator (MINUS_DI), Aroon, Awesome Oscillator (AO), Keltner Channels (KC), Ultimate Oscillator (UO), Commodity Channel Index (CCI), Relative Strength Index (RSI), Fisher Transform of RSI (Fisher_RSI), Stochastic Oscillator (STOCH), Stochastic Fast (STOCHF), Stochastic RSI (STOCHRSI), Moving Average Convergence Divergence (MACD), Money Flow Index (MFI), Rate of Change (ROC), Bollinger Bands (BB), Parabolic SAR (SAR), Triple Exponential Moving Average (TEMA), Hilbert Transform - SineWave (HT_SINE), and Candlestick patterns. In the ElliotV5 strategy, the populate_indicators() function is responsible for calculating and adding these indicators to the input dataframe.
Next, the strategy defines conditions for generating buy signals in the populate_buy_trend() function.
These conditions involve comparing the closing price, moving averages (EMA), Elliott Wave Oscillator (EWO), and RSI with specified thresholds and offsets.
If the conditions are met, a 'buy' signal is assigned to the corresponding rows in the dataframe. Similarly, the populate_sell_trend() function defines conditions for generating sell signals. In this case, the condition involves comparing the closing price with a moving average multiplied by a specified high offset. If the condition is met, a 'sell' signal is assigned to the corresponding rows in the dataframe. Overall, the ElliotV5 strategy uses a combination of technical indicators and predefined conditions to determine buy and sell signals for trading.
Next, the strategy defines conditions for generating buy signals in the populate_buy_trend() function.
These conditions involve comparing the closing price, moving averages (EMA), Elliott Wave Oscillator (EWO), and RSI with specified thresholds and offsets.
If the conditions are met, a 'buy' signal is assigned to the corresponding rows in the dataframe. Similarly, the populate_sell_trend() function defines conditions for generating sell signals. In this case, the condition involves comparing the closing price with a moving average multiplied by a specified high offset. If the condition is met, a 'sell' signal is assigned to the corresponding rows in the dataframe. Overall, the ElliotV5 strategy uses a combination of technical indicators and predefined conditions to determine buy and sell signals for trading.
stoploss: -0.189 timeframe: 5m hash(sha256): 6f5c8582809ed61226540d981a1b6680d710cfc792d4e5e73c2bc28d5bdc0ccf indicators: rsi_buy upper CDLDRAGONFLYDOJI CDLGRAVESTONEDOJI close CDLSPINNINGTOP bb_lowerband sell_signal bb_percent CDL3WHITESOLDIERS kc_middleband volume low_offset retries high fisher_rsi_norma cci ha_high adx aroonosc minus_dm plus_dm ewo_high CDLHANGINGMAN ewo_low aroondown ma_sell_val CDLEVENINGDOJISTAR plus_di ha_open base_nb_candles_buy slowk macdsignal fastk_rsi hma_50 minus_di roc lower rsi sine kc_percent htsine tema uo mfi kc_width macdhist CDLHAMMER htleadsine ma_buy_val CDLEVENINGSTAR sar CDL
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last change: 2024-05-02 15:46:43