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- W3204751792 abstract "In the stock market, trading strategies are commonly utilized to find trading signals to make a more profitable trading, and can be formed by various technical indicators. Based on the correlation of stocks, the pair trading strategy is then developed for trading. The process of a pair trading can be divided into two parts that are finding potential stock pairs and then deriving trading signals, including buying and selling signals. In the process, many parameters should be considered and it is not easy to obtain their appropriate setting. In this paper, we thus propose an approach for finding those parameters by the genetic algorithms. It first encodes the parameters of the correlation coefficient and Bollinger bands into a chromosome. The fitness value of every possible solution is evaluated by the return and number of trading. Experiments are also conducted on real datasets to show that the proposed method is better than the previous one in terms of return." @default.
- W3204751792 created "2021-10-11" @default.
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- W3204751792 date "2021-01-01" @default.
- W3204751792 modified "2023-09-24" @default.
- W3204751792 title "An Effective Correlation-Based Pair Trading Strategy Using Genetic Algorithms" @default.
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- W3204751792 doi "https://doi.org/10.1007/978-3-030-88081-1_19" @default.
- W3204751792 hasPublicationYear "2021" @default.
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