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Circumventing the Computational Hardness of Computational Arbitrage
Olmedo, Author2, Author3, Author4, Author5
computational arbitragemodel performanceallocation problemeconomic insights
2610.40831
Builder Relevance
1d ago70%
Abstract
The paper discusses computational arbitrage in AI model marketplaces, highlighting its potential to create profit opportunities while benefiting consumers and providers.
Reality Card
Core Claim
The authors prove that the optimal allocation for computational arbitrage is NP-hard but can be computed efficiently under certain conditions.
Method / Result
Developed a sample-efficient method for estimating model performance, reducing the upfront cost of identifying arbitrage strategies.
Limitations
The NP-hard nature of the problem may limit the scalability of the proposed methods in larger marketplaces.
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