| Autor: |
Karl Lewis, Mark Anthony Caruana, David Paul Suda |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
AppliedMath, Vol 4, Iss 3, Pp 843-855 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2673-9909 |
| DOI: |
10.3390/appliedmath4030045 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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