Description
Individual investors consistently underperform relevant investment benchmarks. Consequently, a considerable body of literature of fundamental investment strategies targeted towards this audience emerged. Several online platforms provide operationalizations of these strategies in the form of stock screeners. However, each platform must use its own interpretation of the strategy as no central knowledge repository exists. Arguing that ontologies standardize the concepts relevant to a domain and enable knowledge sharing among domain users, this paper seeks to explore that viability of an ontology as a knowledge representation method to represent fundamental investment strategies. Our efforts herein go beyond representing the concepts and inter-concept relationships that are descriptive of fundamental investment strategies, as we also demonstrate that ontologies using SWRL rules can deploy these strategies as stock pickers (also referred to as stock screening). We use the CANSLIM strategy as a case, modeling and executing it on simulated data using our ontology and SWRL.
Recommended Citation
Etudo, Ugochukwu Osemwegie and Al-Abdullah, Muhammad, "An Actionable Knowledge Representation for Popular Fundamental Investment Strategies" (2017). AMCIS 2017 Proceedings. 2.
https://aisel.aisnet.org/amcis2017/SemanticsIS/Presentations/2
An Actionable Knowledge Representation for Popular Fundamental Investment Strategies
Individual investors consistently underperform relevant investment benchmarks. Consequently, a considerable body of literature of fundamental investment strategies targeted towards this audience emerged. Several online platforms provide operationalizations of these strategies in the form of stock screeners. However, each platform must use its own interpretation of the strategy as no central knowledge repository exists. Arguing that ontologies standardize the concepts relevant to a domain and enable knowledge sharing among domain users, this paper seeks to explore that viability of an ontology as a knowledge representation method to represent fundamental investment strategies. Our efforts herein go beyond representing the concepts and inter-concept relationships that are descriptive of fundamental investment strategies, as we also demonstrate that ontologies using SWRL rules can deploy these strategies as stock pickers (also referred to as stock screening). We use the CANSLIM strategy as a case, modeling and executing it on simulated data using our ontology and SWRL.