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The OBOnlyV3 strategy is a trading strategy implemented as a class in Python. It inherits from the IStrategy class. Here is a short description of what the strategy does:
The strategy first populates indicators based on the provided dataframe and metadata.
It checks if indicators need to be computed based on the last computed time and the current dataframe's date.
If indicators need to be computed and protections are enabled, it calculates the 12-day exponential moving average (EMA) and the 26-day EMA for the closing prices and assigns them to the 'ema_12' and 'ema_26' columns of the dataframe.
It defines a list of conditions for entering a buy trade. The conditions include: Randomly selected value between 0 and 2 is 0. The latest closing price is higher than the 12-day EMA. The 12-day EMA is higher than the 26-day EMA. The latest volume is greater than 0. If the conditions are met, the strategy sets a custom condition flag for the specific trading pair in the metadata dictionary to True; otherwise, it sets it to False. The strategy then populates the buy trend based on a random value and the custom conditions flag. If the randomly selected value is 0 and the custom conditions flag for the trading pair is True, the 'buy' column of the dataframe is set to 1; otherwise, it is set to 0. Finally, the strategy populates the sell trend by setting the 'sell' column of the dataframe to 0. Overall, the OBOnlyV3 strategy calculates EMAs, sets conditions for entering a buy trade, and populates the buy and sell trends based on those conditions and random values.
It checks if indicators need to be computed based on the last computed time and the current dataframe's date.
If indicators need to be computed and protections are enabled, it calculates the 12-day exponential moving average (EMA) and the 26-day EMA for the closing prices and assigns them to the 'ema_12' and 'ema_26' columns of the dataframe.
It defines a list of conditions for entering a buy trade. The conditions include: Randomly selected value between 0 and 2 is 0. The latest closing price is higher than the 12-day EMA. The 12-day EMA is higher than the 26-day EMA. The latest volume is greater than 0. If the conditions are met, the strategy sets a custom condition flag for the specific trading pair in the metadata dictionary to True; otherwise, it sets it to False. The strategy then populates the buy trend based on a random value and the custom conditions flag. If the randomly selected value is 0 and the custom conditions flag for the trading pair is True, the 'buy' column of the dataframe is set to 1; otherwise, it is set to 0. Finally, the strategy populates the sell trend by setting the 'sell' column of the dataframe to 0. Overall, the OBOnlyV3 strategy calculates EMAs, sets conditions for entering a buy trade, and populates the buy and sell trends based on those conditions and random values.
startup_candle_count : 100 Recursive Analysis found no issues while using 100 startup_candle_count
stoploss: -0.02 timeframe: 5m hash(sha256): eb635390a305e2dd334722c793570a4c8b80c52d48ce294c5fae838ac527b546 indicators: ratio bids ema_12 b_sum asks a_sum ema_26
No similar strategies found. (based on used indicators)
last change: 2023-08-16 11:42:48