Application Project Jonas Gebele

Retrospectively Identifying Profit-Generating Transactions on the Algorand Blockchain

Abstract

This study systematically identifies arbitrage opportunities within Algorand’s decentralized finance (DeFi) ecosystem,
focusing on Automated Market Maker (AMM) platforms. Utilizing graph algorithms such as Bellman-Ford, alongside
optimization techniques, we introduce a system designed for real-time and historical data arbitrage exploration. While
this initial study focuses on select asset pairs and short time frames, it establishes a framework for future research.
The work combines theoretical and practical insights, suggesting that further refinement and broader implementation
could significantly increase arbitrage profitability.