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The S12 strategy, developed by @Mablue (Masoud Azizi), is a trading strategy implemented in the Freqtrade framework. It utilizes a combination of moving averages and divergence calculations to identify potential buying and selling opportunities in the market. Here are the key components of the strategy:
ROI table: The strategy defines a minimal return on investment (ROI) table that specifies the expected returns at different stages of the trade.
It indicates the target ROI percentages at specific time intervals.
Stoploss: The strategy incorporates a stop-loss mechanism, which helps limit losses by automatically selling a position when it reaches a specified negative threshold.
Buy Parameters: The strategy defines several parameters for the buy signal. These parameters include timeframes for different moving averages (mojoMA, fastMA, and slowMA) and minimum/maximum divergence values. The strategy calculates these indicators using the Ta-Lib library. Sell Parameters: Similarly, the strategy defines parameters for the sell signal, including timeframes for moving averages (fastMA, mojoMA, and slowMA) and minimum/maximum divergence values. The strategy's logic is implemented in three main functions: populate_indicators: This function calculates the moving averages for the specified timeframes and adds them as columns to the dataframe. populate_buy_trend: This function populates the 'buy' column in the dataframe based on specific conditions. It checks if the calculated divergence values for mojoMA and fastMA are within the defined minimum and maximum thresholds, and if the fastMA-to-slowMA divergence is also within the specified range. populate_sell_trend: This function populates the 'sell' column in the dataframe based on conditions similar to the buy signal. It checks if the divergence values for fastMA and mojoMA, as well as the sell-slowMA-to-fastMA divergence, are within the defined thresholds. Overall, the S12 strategy aims to identify buy and sell signals based on moving average crossovers and divergence calculations. It provides a systematic approach for backtesting and evaluating trading performance.
It indicates the target ROI percentages at specific time intervals.
Stoploss: The strategy incorporates a stop-loss mechanism, which helps limit losses by automatically selling a position when it reaches a specified negative threshold.
Buy Parameters: The strategy defines several parameters for the buy signal. These parameters include timeframes for different moving averages (mojoMA, fastMA, and slowMA) and minimum/maximum divergence values. The strategy calculates these indicators using the Ta-Lib library. Sell Parameters: Similarly, the strategy defines parameters for the sell signal, including timeframes for moving averages (fastMA, mojoMA, and slowMA) and minimum/maximum divergence values. The strategy's logic is implemented in three main functions: populate_indicators: This function calculates the moving averages for the specified timeframes and adds them as columns to the dataframe. populate_buy_trend: This function populates the 'buy' column in the dataframe based on specific conditions. It checks if the calculated divergence values for mojoMA and fastMA are within the defined minimum and maximum thresholds, and if the fastMA-to-slowMA divergence is also within the specified range. populate_sell_trend: This function populates the 'sell' column in the dataframe based on conditions similar to the buy signal. It checks if the divergence values for fastMA and mojoMA, as well as the sell-slowMA-to-fastMA divergence, are within the defined thresholds. Overall, the S12 strategy aims to identify buy and sell signals based on moving average crossovers and divergence calculations. It provides a systematic approach for backtesting and evaluating trading performance.
stoploss: -0.128 timeframe: 4h hash(sha256): 483d5c56e769dc9e1d123b65092bc03be688f80f30234d555f711199c1a07ac9
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last change: 2022-07-11 15:31:33