The emergence of blockchain technology has revolutionized the way we think about financial systems. Decentralized finance (DeFi), in particular, has emerged as an alternative to traditional financial systems, providing potentially greater access to financial services and fostering innovation.
Recently a paper was published by researchers from Chulalongkorn Business School, Bangkok, Thailand and Universidad del Rosario, Bogotá, Colombia aimed to map the interconnections among decentralized finance (DeFi) protocols using transactions among contracts and addresses, explore single layer and multiplex network properties and quantify the financial exposure of the most critical nodes.
The paper underlines that financial networks tend to have the following characteristics, predominantly sparse, with heavy-tailed degree distributions, and high clustering, with short average path length. To study the data the researchers used both single-layer and multiplex networks. The findings indicated that the DeFi networks share similar scale-free properties as those of other networks.
The research further performed Protocol Network Visualization, it highlighted that the graph visualization of the reduced protocol network is relatively straightforward to understand. In addition, the edges for each of the five tokens are shown separately to demonstrate the layers of the relationship. Each node in the network represents a unique named protocol or entity, and node size represents the financial exposure measured as outstanding balances in USD at the end of the corresponding month.
Further, it discussed Higher-Frequency Changes in Centrality, the report underscores that various centrality measures are employed to understand the importance and influence of nodes within the network. It compared five commonly used centrality measures these include closeness centrality, betweenness centrality, eigenvector centrality, Katz centrality, and PageRank. Closeness centrality quantifies how quickly a node can reach other nodes in the network. Nodes with high closeness centrality have short average distances to all other nodes, indicating their potential to disseminate information or resources efficiently.
Eigenvector centrality assigns importance to nodes based on their connections to other high-scoring nodes. It considers not only the number of connections but also the quality of those connections. Nodes with high eigenvector centrality are connected to other important nodes, reflecting their influence and prominence in the network.
Katz centrality measures the influence of a node by considering not only its direct connections but also the contributions from its neighbours. It assigns higher importance to nodes that have connections to other important nodes. PageRank is a centrality measure inspired by Google’s web page ranking algorithm. Similar to Katz’s centrality, it classifies a node as important if it is highly linked to other nodes but also emphasizes the quality of the incoming links. The paper examines the temporal evolution of centrality, highlighting the protocols facilitating resource intermediation across the network and serving as core functional components supporting compositions within this technological stack.
The paper concludes that the scale-free nature of the DeFi protocol network, similar to other financial networks, suggests a mechanism such as preferential attachment. The resemblance of the DeFi protocol network to traditional institutional networks, including interbank networks that have been extensively studied and monitored by regulatory bodies, is reassuring and intriguing. On the one hand, this similarity enables supervisors to implement macroprudential tools that have proven effective in traditional finance. Additionally, it offers a fertile ground for academics to deepen their understanding of this ecosystem. Despite the ease with which new protocols can compete with similar business models based on services offered through smart contracts, existing protocols maintain their significance within the network.
