Drake, Rachel and Moodley, Deshendran (2022) INVEST: Ontology Driven Bayesian Networks for Investment Decision Making on the JSE, Proceedings of Second Southern African Conference for Artificial Intelligence Research, 6-10 December 2021, Online, 252-273.
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Abstract
This research proposes an architecture and prototype implementation of a knowledge-based system for automating share evaluation and investment decision making on the Johannesburg Stock Exchange (JSE). The knowledge acquired from an analysis of the investment domain for a value investing approach is represented in an ontology. A Bayesian network, developed using the ontology, is used to capture the complex causal relations between different factors that influence the quality and value of individual shares. The system was found to adequately represent the decision-making process of investment professionals and provided superior returns to selected benchmark JSE indices from 2012 to 2018.
| Item Type: | Conference paper |
|---|---|
| Subjects: | Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Probabilistic reasoning Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Ontology engineering Applied computing > Operations research > Decision analysis |
| Date Deposited: | 29 Apr 2022 05:47 |
| Last Modified: | 29 Apr 2022 05:47 |
| URI: | https://pubs.cs.uct.ac.za/id/eprint/1526 |
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