Network Graph Analysis is a quantitative method that applies graph theory to model and examine relationships, connections, and interactions within complex systems, such as blockchain transaction flows or inter-firm trading networks. This analytical approach provides a visual and mathematical representation of systemic structures. Its purpose is to identify patterns, anomalies, and influential entities.
Mechanism
The mechanism involves representing entities (e.g., crypto addresses, trading accounts, market participants) as ‘nodes’ and their interactions (e.g., transactions, communication links, trade relationships) as ‘edges’ within a graph structure. Algorithms then compute metrics like centrality, density, and clustering coefficients to quantify the network’s properties and the significance of individual nodes.
Methodology
This methodology is deployed in crypto investing to detect illicit activities, trace the movement of funds, identify market manipulation schemes, and assess systemic risk by mapping transactional dependencies. For Request for Quote (RFQ) crypto and institutional options trading, it can reveal hidden relationships between counterparties or detect coordinated trading behaviors, thereby enhancing risk surveillance and compliance efforts.
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