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Long- and Medium-Term Financial Strategies on Equities Using Dynamic Bayesian Networks

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Title: Long- and Medium-Term Financial Strategies on Equities Using Dynamic Bayesian Networks
Authors: Karl Lewis, Mark Anthony Caruana, David Paul Suda
Source: AppliedMath, Vol 4, Iss 3, Pp 843-855 (2024)
Publisher Information: MDPI AG, 2024.
Publication Year: 2024
Collection: LCC:Mathematics
Subject Terms: finance, dynamic Bayesian networks, trading strategies, equities, Mathematics, QA1-939
More Details: Devising a financial trading strategy that allows for long-term gains is a very common problem in finance. This paper aims to formulate a mathematically rigorous framework for the problem and compare and contrast the results obtained. The main approach considered is based on Dynamic Bayesian Networks (DBNs). Within the DBN setting, a long-term as well as a short-term trading strategy are considered and applied on twelve equities obtained from developed and developing markets. It is concluded that both the long-term and the medium-term strategies proposed in this paper outperform the benchmark buy-and-hold (B&H) trading strategy. Despite the clear advantages of the former trading strategies, the limitations of this model are discussed along with possible improvements.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2673-9909
Relation: https://www.mdpi.com/2673-9909/4/3/45; https://doaj.org/toc/2673-9909
DOI: 10.3390/appliedmath4030045
Access URL: https://doaj.org/article/894389c81e9a48229fbe91f6e922d522
Accession Number: edsdoj.894389c81e9a48229fbe91f6e922d522
Database: Directory of Open Access Journals
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  Data: Long- and Medium-Term Financial Strategies on Equities Using Dynamic Bayesian Networks
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  Data: AppliedMath, Vol 4, Iss 3, Pp 843-855 (2024)
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  Data: Devising a financial trading strategy that allows for long-term gains is a very common problem in finance. This paper aims to formulate a mathematically rigorous framework for the problem and compare and contrast the results obtained. The main approach considered is based on Dynamic Bayesian Networks (DBNs). Within the DBN setting, a long-term as well as a short-term trading strategy are considered and applied on twelve equities obtained from developed and developing markets. It is concluded that both the long-term and the medium-term strategies proposed in this paper outperform the benchmark buy-and-hold (B&H) trading strategy. Despite the clear advantages of the former trading strategies, the limitations of this model are discussed along with possible improvements.
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        PageCount: 13
        StartPage: 843
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        Type: general
      – SubjectFull: dynamic Bayesian networks
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      – SubjectFull: trading strategies
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      – SubjectFull: equities
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              Y: 2024
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