Systemic Risk Analysis of Synthetic Asset Issuance Protocols in Decentralized Finance (DeFi) Networks Based on Network Analysis and On-Chain Data

Abstract

Title: Systemic Risk Analysis of Synthetic Asset Issuance Protocols in Decentralized Finance (DeFi) Networks Based on Network Analysis and On-Chain Data DBA Candidate, University of Tehran Abstract: This study aims to analyze the systemic risk of synthetic asset issuance protocols within Iranian Decentralized Finance (DeFi) networks. To this end, a network analysis and on-chain data approach was employed to investigate financial interdependencies among key domestic cryptocurrency platforms, including Ramzinex, Nobitex, Bit24, Phintra, and IranExChain. Real-world data from 382,747 transactions spanning from March to December 2024 (Farvardin to Azar 1403 SH) were extracted and modeled as a cross-platform transaction matrix. Network analysis results indicate that the structure of Iran’s decentralized financial ecosystem is scale-free and heterogeneous, and liquidity concentration in two primary nodes (Ramzinex = 0.62, Nobitex = 0.51) significantly increases the probability of financial contagion among protocols. The network propagation model, with transmission coefficients β=0.16\beta = 0.16β=0.16 and γ=0.09\gamma = 0.09γ=0.09, demonstrates that under a scenario of a 30% drop in collateral value, the ratio of infected nodes to the entire network increases. The composite Network Stability Index (NSI), valued at 0.74 under normal conditions and 0.46 under severe shocks, confirms the transition of the system into a fragility phase. Sensitivity and bootstrap analyses recorded an error of 0.038, validating the robustness of the model. Furthermore, results show that the introduction of the digital Rial (Rial Digital Currency) in June 2024 led to a 12% reduction in average systemic risk and enhanced cross-platform stability. Based on the findings, three strategies are proposed to mitigate systemic risk in Iran’s DeFi ecosystem: improving on-chain data transparency, regulating Rial-based collateralization policies, and designing an early warning system based on the SIR model. By combining local on-chain data with international network metrics, this study presents the first comprehensive analytical framework for assessing financial resilience in Iranian synthetic asset protocols. Keywords: Systemic Risk, Synthetic Assets, Decentralized Finance (DeFi), Network Analysis, On-Chain Data, Stability Index, Rial Digital Currency, SIR Model.