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The Elliot strategy is a trading strategy that utilizes various indicators to determine buying and selling opportunities. Here's a breakdown of what the strategy does:
populate_indicators: This method calculates and populates several indicators on the input dataframe. Some of the indicators used include moving averages, Bollinger Bands, Hull Moving Average, Exponential Moving Average (EMA), Exponential Weighted Oscillator (EWO), MACD, and RSI (Relative Strength Index).
populate_buy_trend: This method identifies potential buy signals based on specific conditions.
The conditions checked include an uptrend in the 1-hour timeframe, a low RSI value, the close price being below a certain moving average (ma_buy), a high EWO value, a low RSI value (rsi_buy), and positive volume.
If the conditions are met, the dataframe is updated with a "buy" signal and a corresponding tag. populate_sell_trend: This method identifies potential sell signals based on specific conditions. The conditions checked include the relationship between the SMA (Simple Moving Average) and HMA (Hull Moving Average), the close price being above a certain moving average (ma_sell), the RSI value being above 50, and positive volume. If the conditions are met, the dataframe is updated with a "sell" signal. Overall, the Elliot strategy aims to identify buy signals when certain criteria are met, and sell signals when other criteria are satisfied. It uses a combination of technical indicators to make these determinations and can be used for backtesting trading strategies on historical data.
populate_buy_trend: This method identifies potential buy signals based on specific conditions.
The conditions checked include an uptrend in the 1-hour timeframe, a low RSI value, the close price being below a certain moving average (ma_buy), a high EWO value, a low RSI value (rsi_buy), and positive volume.
If the conditions are met, the dataframe is updated with a "buy" signal and a corresponding tag. populate_sell_trend: This method identifies potential sell signals based on specific conditions. The conditions checked include the relationship between the SMA (Simple Moving Average) and HMA (Hull Moving Average), the close price being above a certain moving average (ma_sell), the RSI value being above 50, and positive volume. If the conditions are met, the dataframe is updated with a "sell" signal. Overall, the Elliot strategy aims to identify buy signals when certain criteria are met, and sell signals when other criteria are satisfied. It uses a combination of technical indicators to make these determinations and can be used for backtesting trading strategies on historical data.
stoploss: -0.32 timeframe: 5m hash(sha256): 35673a0bbfacb689df0a65be2a4a8e3990624e49fd7bb90de2cd1e558cb33019
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last change: 2022-10-02 19:17:59