An Optimization Approach for Finding Diverse Trading Strategy Portfolio Using the Memetic Algorithm

Trading strategies are usually employed to find trading signals for maximizing return and reducing risk as well. As a result, many approaches have been proposed for obtaining a trading strategy portfolio (TSP). An existing optimization approach has been proposed for generating an appropriate TSP based on the given technical indicators. However, the diversity of the generated TSP should be enhanced because the financial market can be influenced by various factors. Therefore, taking the concept of a technical indicator pool (TIP) into consideration, an enhanced optimization algorithm is proposed to generate more potential candidate trading strategies for increasing the diversity of a TSP using the memetic algorithm. To reach this goal, a new fitness function that can make the genetic makeup of each more diverse is designed. At last, experiments were made on the real datasets to show the effectiveness of the proposed approach.