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A novel approach to portfolio selection using news volume and sentiment

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  • Kin‐Yip Ho
  • Kun Tracy Wang
  • Wanbin Walter Wang

Abstract

In this study, we develop a novel approach to portfolio diversification by integrating information on news volume and sentiment with the k‐nearest neighbors (kNN) algorithm. Our empirical analysis indicates that high news volume contributes to portfolio risk, whereas news sentiment contributes to portfolio return. Based on these findings, we propose a kNN algorithm for portfolio selection. Our in‐sample and out‐of‐sample tests suggest that the proposed kNN portfolio selection approach outperforms the benchmark index portfolio. Overall, we show that incorporating news volume and sentiment into portfolio selection can enhance portfolio performance by improving returns and reducing risk.

Suggested Citation

  • Kin‐Yip Ho & Kun Tracy Wang & Wanbin Walter Wang, 2023. "A novel approach to portfolio selection using news volume and sentiment," International Review of Finance, International Review of Finance Ltd., vol. 23(4), pages 903-917, December.
    • Handle: RePEc:bla:irvfin:v:23:y:2023:i:4:p:903-917
    DOI: 10.1111/irfi.12427
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    References listed on IDEAS

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    4. Anil Bera & Sung Park, 2008. "Optimal Portfolio Diversification Using the Maximum Entropy Principle," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 484-512.
    5. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    6. Zhang, Junru & Zhang, Zhaoyong, 2021. "CSR, Media and Stock Illiquidity: Evidence from Chinese Listed Financial Firms," Finance Research Letters, Elsevier, vol. 41(C).
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