| 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 |
