The GuruSkippyasurmuni strategy is a trading strategy implemented as a class that inherits from the IStrategy interface. It has several methods that perform specific tasks within the strategy. The populate_indicators method is responsible for populating indicators in the given dataframe.
It retrieves the trading pair from the metadata and initializes custom information if it doesn't exist.
The method returns the updated dataframe.
The should_long method is used to determine whether a long position should be taken based on the current profit. If the current profit is less than 0.01, it returns False; otherwise, it returns True. The should_short method is not provided in the code snippet. The sizing method is responsible for determining the stake amount for a trade based on the proposed stake, minimum stake, and maximum stake. It simply returns the proposed stake value. The stop_loss method is not provided in the code snippet. The populate_buy_trend method populates the buy signals in the dataframe based on multiple conditions. It retrieves indicator values and operators from different variables and uses a helper function called condition_generator to generate conditions. The resulting conditions are appended to a list, and if any conditions exist, the corresponding rows in the dataframe are marked as a buy signal. The populate_sell_trend method is similar to populate_buy_trend but populates sell signals instead. It retrieves sell indicator values and operators from variables, generates conditions using condition_generator, appends conditions to a list, and marks corresponding rows in the dataframe as a sell signal if any conditions exist. Overall, the strategy performs indicator population, determines long positions, stake sizing, and generates buy and sell signals based on specified conditions.
It retrieves the trading pair from the metadata and initializes custom information if it doesn't exist.
The method returns the updated dataframe.
The should_long method is used to determine whether a long position should be taken based on the current profit. If the current profit is less than 0.01, it returns False; otherwise, it returns True. The should_short method is not provided in the code snippet. The sizing method is responsible for determining the stake amount for a trade based on the proposed stake, minimum stake, and maximum stake. It simply returns the proposed stake value. The stop_loss method is not provided in the code snippet. The populate_buy_trend method populates the buy signals in the dataframe based on multiple conditions. It retrieves indicator values and operators from different variables and uses a helper function called condition_generator to generate conditions. The resulting conditions are appended to a list, and if any conditions exist, the corresponding rows in the dataframe are marked as a buy signal. The populate_sell_trend method is similar to populate_buy_trend but populates sell signals instead. It retrieves sell indicator values and operators from variables, generates conditions using condition_generator, appends conditions to a list, and marks corresponding rows in the dataframe as a sell signal if any conditions exist. Overall, the strategy performs indicator population, determines long positions, stake sizing, and generates buy and sell signals based on specified conditions.
stoploss: -1 timeframe: 5m hash(sha256): 03b2ca163d7742b6a7bc140259583c5d5312afe0a2bdabf86da6acfbcafc9b2d indicators: volume indicator_trend_sma crossed_indicator date indicator buy sharp_indicator
No similar strategies found. (based on used indicators)
last change: 2024-04-28 08:41:51