The "pmaxTest" strategy is designed to backtest various trading indicators and conditions. Here's a brief description of what the strategy does:
The "populate_indicators" function calculates and adds several indicators to the input dataframe, including Heikin-Ashi candles, volume, pmax values, source price, pmax threshold, RSI (Relative Strength Index), TRIMA, ZEMA, RMI (Rahul Mohindar Oscillator), and CCI (Commodity Channel Index). The "populate_buy_trend" function generates buy signals based on specific conditions.
It sets the "buy" column of the dataframe to 1 when the following conditions are met: The TRIMA value crosses above the ZEMA value.
TRIMA and ZEMA values are greater than the pmax value.
RMI is less than 50. CCI is less than or equal to -91. Fast %K of Stochastic RSI is less than 41. The closing price is at least 10% higher than the highest closing price in the last 288 periods. RSI (fast) is less than 35. RSI (84-period) is less than 60. RSI (112-period) is less than 60. Volume is greater than 0. The "populate_sell_trend" function generates sell signals based on the condition that volume is greater than 0. It sets the "sell" column of the dataframe to 0. The remaining code defines and calculates various moving averages (MA) based on different MA types and lengths. The ATR (Average True Range) is calculated based on the given period. Upper and lower bands are calculated based on the MA value and the ATR multiplier. The final upper and lower bands are determined based on the previous values and the current MA value. The "pm" (pmax) array is calculated based on the final upper and lower bands and the MA value. The "pmx" array indicates whether the price is trending up or down based on the pmax values. The strategy combines these indicators and conditions to generate buy and sell signals for backtesting trading strategies.
It sets the "buy" column of the dataframe to 1 when the following conditions are met: The TRIMA value crosses above the ZEMA value.
TRIMA and ZEMA values are greater than the pmax value.
RMI is less than 50. CCI is less than or equal to -91. Fast %K of Stochastic RSI is less than 41. The closing price is at least 10% higher than the highest closing price in the last 288 periods. RSI (fast) is less than 35. RSI (84-period) is less than 60. RSI (112-period) is less than 60. Volume is greater than 0. The "populate_sell_trend" function generates sell signals based on the condition that volume is greater than 0. It sets the "sell" column of the dataframe to 0. The remaining code defines and calculates various moving averages (MA) based on different MA types and lengths. The ATR (Average True Range) is calculated based on the given period. Upper and lower bands are calculated based on the MA value and the ATR multiplier. The final upper and lower bands are determined based on the previous values and the current MA value. The "pm" (pmax) array is calculated based on the final upper and lower bands and the MA value. The "pmx" array indicates whether the price is trending up or down based on the pmax values. The strategy combines these indicators and conditions to generate buy and sell signals for backtesting trading strategies.
startup_candle_count : 50 pm: -0.001% rsi: 0.539% rsi_fast: 0.002% rmi: 0.135%
stoploss: -0.99 timeframe: 5m hash(sha256): 22c0866f30509350927816bcecd7c74da9ed6441b08013850364c65493dace38 indicators: basic_ub close pmx fastk rsi_fast srsi_fk volume srsi_fd rsi_84 source open fastd rmi pmax_thresh high rsi_112 cci final_ub pm basic_lb zema_buy final_lb rsi low trima_buy
No similar strategies found. (based on used indicators)
last change: 2024-05-02 10:04:07