The "TaSearch1m" strategy is designed to backtest trading strategies using historical price data. Here's a short description of what the strategy does:
The strategy uses the "TaSearch" module for technical analysis calculations. It initializes variables for the number of periods (n) and the percentage threshold (p) for determining buy and sell signals.
The strategy sets a minimal return on investment (ROI) target and a stop loss threshold.
The "populate_indicators" function processes the price data and adds additional columns to the DataFrame.
It uses the "TaSearch" module to find extremes in the data. The "populate_buy_trend" function sets the "buy" column to 1 where there is a "buy" signal. The "populate_sell_trend" function sets the "sell" column to 1 where there is a "sell" signal and adds an "exit_tag" column to indicate the reason for selling. The "confirm_trade_exit" function is used to validate trade exits. It checks if the exit reason is an "exit_signal" and if the trade's profit ratio is negative. If it is, the trade is rejected. The "__populate_buy" function determines whether to generate a "buy" signal based on specific conditions involving the "ex_min_percentage" and "rsi_7" indicators. The "__populate_sell" function determines whether to generate a "sell" signal based on specific conditions involving the "rsi_7," "macd," "macdsignal," and "macdhist" indicators. Overall, the strategy aims to identify buying and selling opportunities based on technical indicators and validate trade exits to optimize trading performance.