This study presents the preliminary results of an Ontology for ‘Financial Events’, which provides a formal framework for categorizing events impacting financial markets. This paper outlines its development, drawing from established methodologies and prior research on event representation (particularly, the UFO-B top ontology). The ontology, implemented using OWL language, includes concepts for various financial events and their causal relationships. Validation involved testing logical consistency and expert review. Challenges included managing event complexity. The ontology facilitates data analysis and interpretation for applications such as risk analysis and trend forecasting. Future research will focus on refinement and integration with text mining and machine learning techniques for enhanced predictive modeling in financial asset management.