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The "OBOnly" strategy is designed for backtesting trading strategies on a website. Here's a short description of what this strategy does:
The strategy uses the Freqtrade library and implements the "IStrategy" interface. It defines a minimal return on investment (ROI) for different time periods.
The stop loss is disabled in this strategy.
The timeframe for analysis is set to 1 hour.
The strategy requires a startup candle count of 50 before producing valid signals. It defines several variables related to order book analysis, such as history, delta bid/ask, ratio, blend, and log. The "confirm_trade_entry" function is called to determine whether to enter a trade. It retrieves the order book data, calculates bid and ask cut-off prices based on the mid-price, and calculates bid and ask side volumes. If certain conditions are met, the function returns True to initiate a trade. The "populate_indicators" function is empty and does not populate any additional indicators. The "populate_buy_trend" function sets a "buy" flag to 1 in the DataFrame, indicating a buy signal. The "populate_sell_trend" function sets a "sell" flag to 0 in the DataFrame, indicating no sell signal. Overall, the strategy focuses on analyzing the order book and initiating trades based on specific conditions related to bid/ask volumes and historical ratios. It provides minimal ROI targets for different time periods and sets up the necessary indicators for backtesting.
The stop loss is disabled in this strategy.
The timeframe for analysis is set to 1 hour.
The strategy requires a startup candle count of 50 before producing valid signals. It defines several variables related to order book analysis, such as history, delta bid/ask, ratio, blend, and log. The "confirm_trade_entry" function is called to determine whether to enter a trade. It retrieves the order book data, calculates bid and ask cut-off prices based on the mid-price, and calculates bid and ask side volumes. If certain conditions are met, the function returns True to initiate a trade. The "populate_indicators" function is empty and does not populate any additional indicators. The "populate_buy_trend" function sets a "buy" flag to 1 in the DataFrame, indicating a buy signal. The "populate_sell_trend" function sets a "sell" flag to 0 in the DataFrame, indicating no sell signal. Overall, the strategy focuses on analyzing the order book and initiating trades based on specific conditions related to bid/ask volumes and historical ratios. It provides minimal ROI targets for different time periods and sets up the necessary indicators for backtesting.
startup_candle_count : 50 Recursive Analysis found no issues while using 50 startup_candle_count
stoploss: -0.01 timeframe: 1h hash(sha256): 0fbca18bd6ba777c616d982777e4513eb3727b90ef256cc9dfee71c8acb1af7a indicators: asks bids a_sum b_sum
No similar strategies found. (based on used indicators)
last change: 2023-09-29 22:19:10