Parametric portfolio policy with momentum-based sentiment trading strategy

Wen-Yi Lee, Yu-Hsuan Lin, Jing-Rung Yu and Donald Lien

PLOS ONE, 2025, vol. 20, issue 11, 1-12

Abstract: To enhance the effectiveness of the conventional mean-variance portfolio model, this study introduces a parametric portfolio policy that incorporates a momentum-based sentiment characteristic vector. This vector enables the identification of outperforming assets by capturing both historical returns and market sentiment. Drawing on a decade of rebalancing data from the S&P 500 and Dow Jones 30 constituent stocks, the proposed model optimizes the interrelationships among portfolio holdings, a benchmark portfolio, and the constructed characteristic vectors. In contrast to conventional static back testing approaches, the proposed model accounts for transaction costs and is evaluated over a 15-year investment horizon. Empirical results demonstrate that the proposed model significantly outperforms the benchmark, particularly the minimum-variance model that does not incorporate sentiment-driven parametric adjustments. During periods of financial crisis, the model selects sentiment-based momentum more frequently, leading to differing asset allocations and potentially higher utility for investors. The sentiment-augmented momentum strategy exhibits superior performance compared to the conventional mean-variance approach. The findings underscore the importance of integrating market sentiment into characteristic vector construction, affirming the value of parametric portfolio policies in improving asset allocation and risk-adjusted returns.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0335462

DOI: 10.1371/journal.pone.0335462

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