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Stock market prediction using Altruistic Dragonfly Algorithm

Author

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  • Bitanu Chatterjee
  • Sayan Acharya
  • Trinav Bhattacharyya
  • Seyedali Mirjalili
  • Ram Sarkar

Abstract

Stock market prediction is the process of determining the value of a company’s shares and other financial assets in the future. This paper proposes a new model where Altruistic Dragonfly Algorithm (ADA) is combined with Least Squares Support Vector Machine (LS-SVM) for stock market prediction. ADA is a meta-heuristic algorithm which optimizes the parameters of LS-SVM to avoid local minima and overfitting, resulting in better prediction performance. Experiments have been performed on 12 datasets and the obtained results are compared with other popular meta-heuristic algorithms. The results show that the proposed model provides a better predictive ability and demonstrate the effectiveness of ADA in optimizing the parameters of LS-SVM.

Suggested Citation

  • Bitanu Chatterjee & Sayan Acharya & Trinav Bhattacharyya & Seyedali Mirjalili & Ram Sarkar, 2023. "Stock market prediction using Altruistic Dragonfly Algorithm," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-20, April.
    • Handle: RePEc:plo:pone00:0282002
    DOI: 10.1371/journal.pone.0282002
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