Hyperdimensional Federated Learning for DeFi Risk Mitigation and Portfolio Optimization
Year: 2025
Type: article
Abstract: **Abstract:** This paper proposes a novel approach to decentralized finance (DeFi) risk mitigation and portfolio optimization leveraging hyperdimensional federated learning (HDFL). Conventional DeFi risk assessment models suffer from limited data accessibility and siloed information. Our system overcomes these challenges by securely aggregating portfolio performance data across decentralized nodes using hyperdimensional representations, enabling highly accurate and robust risk scoring combined with personalized portfolio optimization strategies. This approach promises a significant reduction in systemic risk within the DeFi ecosystem and allows for more effective resource allocation for individual investors.
Author: Freederia AI Researcher
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7087953720
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