The "TaSearch5mL" strategy is designed for backtesting trading strategies. It uses technical analysis indicators and a custom search algorithm to identify potential buy signals and exit signals for trading on a 5-minute timeframe. Here are the important parts of the strategy:
The strategy initializes with a search object called "TaSearch" which uses a specific set of parameters (n and p) for its operations.
The strategy populates indicators by preprocessing the input DataFrame.
It renames the columns and applies the "find_extremes" method from the search object.
The "buy_past_rsi" method iterates over the DataFrame in reverse order and checks for certain conditions to identify potential buy signals based on past relative strength index (RSI) values. The "buy_stride" method also iterates over the DataFrame in reverse order and identifies potential buy signals based on RSI values and the difference between the current index and a previous index. The strategy populates the entry trend by setting the "buy" column to 1 for rows that meet specific conditions related to the "buy_stride," "buy_past_rsi," and "market" columns. The strategy populates the exit trend by setting the "sell" column to 1 for rows that meet specific conditions based on RSI values. The strategy includes a method called "leverage" that allows customization of leverage for each new trade in futures mode. The strategy includes a method called "confirm_trade_exit" that determines whether a trade should be exited based on certain conditions, including the exit reason and the profit ratio. Overall, the TaSearch5mL strategy aims to identify potential buy signals based on RSI values and other indicators, and exit trades based on specific conditions. It sets a fixed leverage of 5 for each trade in futures mode.
The strategy populates indicators by preprocessing the input DataFrame.
It renames the columns and applies the "find_extremes" method from the search object.
The "buy_past_rsi" method iterates over the DataFrame in reverse order and checks for certain conditions to identify potential buy signals based on past relative strength index (RSI) values. The "buy_stride" method also iterates over the DataFrame in reverse order and identifies potential buy signals based on RSI values and the difference between the current index and a previous index. The strategy populates the entry trend by setting the "buy" column to 1 for rows that meet specific conditions related to the "buy_stride," "buy_past_rsi," and "market" columns. The strategy populates the exit trend by setting the "sell" column to 1 for rows that meet specific conditions based on RSI values. The strategy includes a method called "leverage" that allows customization of leverage for each new trade in futures mode. The strategy includes a method called "confirm_trade_exit" that determines whether a trade should be exited based on certain conditions, including the exit reason and the profit ratio. Overall, the TaSearch5mL strategy aims to identify potential buy signals based on RSI values and other indicators, and exit trades based on specific conditions. It sets a fixed leverage of 5 for each trade in futures mode.
stoploss: 55 timeframe: 5m hash(sha256): 7d8f894186b8755f24ba809305b3ff9294672b314fc6241e4ba6f85870d1410d
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last change: 2024-04-28 00:19:41