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The ElliotV5HOMod1 strategy is a backtesting strategy that utilizes various indicators to make buying and selling decisions in a trading system. Here is a brief description of what the strategy does:
The populate_indicators function calculates several indicators, including moving averages (MA), EWO (Elliott Wave Oscillator), and RSI (Relative Strength Index), based on the provided input dataframe. The populate_buy_trend function determines the conditions for buying by setting up multiple criteria:
a.
If the closing price is lower than a specific moving average multiplied by a low offset value, EWO is higher than a specified threshold, RSI is lower than a specified value, and the trading volume is greater than zero, a buy signal is generated.
b.
If the closing price is lower than a specific moving average multiplied by a low offset value, EWO is lower than a specified threshold, and the trading volume is greater than zero, a buy signal is generated. The function updates the 'buy' column in the dataframe with the buy signals. The populate_sell_trend function determines the conditions for selling: If the closing price is higher than a specific moving average multiplied by a high offset value and the trading volume is greater than zero, a sell signal is generated. The function updates the 'sell' column in the dataframe with the sell signals. The current_profit function calculates the current profit based on the last analyzed dataframe and the open date of the trade. If the current profit is less than 0.001 and the current time is more than 140 minutes after the trade's open date, a negative profit of -0.005 is returned; otherwise, a profit of 1 is returned. Overall, the strategy combines moving averages, EWO, RSI, and volume analysis to determine buying and selling signals in a backtesting environment.
If the closing price is lower than a specific moving average multiplied by a low offset value, EWO is higher than a specified threshold, RSI is lower than a specified value, and the trading volume is greater than zero, a buy signal is generated.
b.
If the closing price is lower than a specific moving average multiplied by a low offset value, EWO is lower than a specified threshold, and the trading volume is greater than zero, a buy signal is generated. The function updates the 'buy' column in the dataframe with the buy signals. The populate_sell_trend function determines the conditions for selling: If the closing price is higher than a specific moving average multiplied by a high offset value and the trading volume is greater than zero, a sell signal is generated. The function updates the 'sell' column in the dataframe with the sell signals. The current_profit function calculates the current profit based on the last analyzed dataframe and the open date of the trade. If the current profit is less than 0.001 and the current time is more than 140 minutes after the trade's open date, a negative profit of -0.005 is returned; otherwise, a profit of 1 is returned. Overall, the strategy combines moving averages, EWO, RSI, and volume analysis to determine buying and selling signals in a backtesting environment.
stoploss: -0.3 timeframe: 5m hash(sha256): 61d42754c87b330904d56d6aab82b0f766de63bc1c7bfdac106457d52bc5ea2a indicators: rsi_buy ma_sell_val volume EWO ewo_high low_offset close ewo_low rsi high_offset base_nb_candles_sell runmode base_nb_candles_buy ma_buy_val
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last change: 2022-07-02 19:54:08