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The SMAOG strategy is a trading strategy that uses Simple Moving Average (SMA) and Exponential Moving Average (EMA) indicators to generate buy and sell signals. Here's a breakdown of what the strategy does:
Import necessary libraries and modules. Define a dictionary of moving average types, including SMA and EMA.
Define the SMAOG class that implements the Freqtrade IStrategy interface.
Set the version of the strategy interface to 2.
Define parameters for buying and selling, including base number of candles, trigger types, offsets, and thresholds. Define additional parameters for the strategy, such as timeframe, stop loss, minimal ROI, trailing stop, and more. Implement the populate_indicators method to calculate various indicators using the provided DataFrame. Implement the populate_buy_trend method to determine the buy signals based on specific conditions, including the crossover of moving averages, close price relative to moving average offset, and volume. Implement the populate_sell_trend method to determine the sell signals based on specific conditions, including the close price relative to the moving average offset, RSI values, and volume. Overall, the strategy aims to generate buy signals when the short-term moving average crosses above the long-term moving average, the price is below the moving average offset, and certain thresholds are met. It generates sell signals when the price is above the moving average offset and specific conditions related to RSI and previous candle prices are satisfied.
Define the SMAOG class that implements the Freqtrade IStrategy interface.
Set the version of the strategy interface to 2.
Define parameters for buying and selling, including base number of candles, trigger types, offsets, and thresholds. Define additional parameters for the strategy, such as timeframe, stop loss, minimal ROI, trailing stop, and more. Implement the populate_indicators method to calculate various indicators using the provided DataFrame. Implement the populate_buy_trend method to determine the buy signals based on specific conditions, including the crossover of moving averages, close price relative to moving average offset, and volume. Implement the populate_sell_trend method to determine the sell signals based on specific conditions, including the close price relative to the moving average offset, RSI values, and volume. Overall, the strategy aims to generate buy signals when the short-term moving average crosses above the long-term moving average, the price is below the moving average offset, and certain thresholds are met. It generates sell signals when the price is above the moving average offset and specific conditions related to RSI and previous candle prices are satisfied.
startup_candle_count : 400 ema_200: -0.013%
stoploss: -0.23 timeframe: 5m hash(sha256): f15883b855beb84552ffb902e8db306c2c43f9529c20942e0076014b7b8dc5d2 indicators: volume ema_200 ema_50 low_offset _is_bad ma_offset_sell close sell_trigger ma_offset_buy high_offset buy_trigger base_nb_candles_sell runmode open rsi_exit base_nb_candles_buy
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last change: 2023-11-02 22:00:18