Davide Mancino, Hasret Ozan Sevim, Oriol Saguillo Gonzalez
This student paper introduces a novel methodology for the detection and analysis of multihop cross-chain arbitrage opportunities, wherein multihop denotes arbitrage sequences involving more than two transactional steps across distinct blockchain networks, executed using sequence-dependent strategies. Utilizing a comprehensive dataset comprising over 2.4 billion transactions recorded between September 2023 and August 2024 (encompassing 12 blockchain platforms and 45 cross-chain bridges) we design and implement an algorithm capable of identifying, sequence-dependent arbitrage paths spanning multiple ecosystems. Our empirical analysis demonstrates that such arbitrage opportunities are exceedingly infrequent, underscoring the inherent challenges associated with multihop execution in cross-chain environments.
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