Integrating Market Microstructure Mechanisms into Financial Knowledge Graphs: A Semantic Modeling Approach

Abstract

The rapid evolution of financial markets necessitates advanced data representation techniques that can capture both macro-level entity relationships and micro-level trading dynamics. Traditional Financial Knowledge Graphs (FKGs) have primarily focused on static or slow-moving data, such as corporate hierarchies, industry classifications, and supply chain links. However, these structures often fail to incorporate the high-frequency, granular insights provided by market microstructure mechanisms, including order flow toxicity, liquidity fluctuations, and price discovery processes. This research proposes a novel semantic modeling approach to integrate market microstructure mechanisms into a unified Financial Knowledge Graph framework. By developing a specialized ontology that defines classes for limit order book events, participant behaviors, and execution patterns, the study enables the transformation of raw high-frequency trading data into structured semantic triples. The methodology involves a multi-stage process: first, the design of a temporal-aware ontology; second, the extraction of microstructure features using signal processing techniques; and third, the fusion of these features into an existing knowledge graph using graph embedding algorithms. Experimental results demonstrate that the integrated model significantly improves the representation of market states and enhances the predictive power of the graph for short-term volatility and liquidity risk. The findings suggest that semantic modeling provides a robust bridge between qualitative financial knowledge and quantitative market mechanics. This integration allows for a more holistic understanding of market fragility and the interconnectedness of financial assets under high-frequency conditions. The study concludes that incorporating microstructure dynamics into knowledge graphs is essential for the next generation of intelligent financial monitoring and algorithmic decision-support systems, offering a scalable solution for real-time market analysis.