Optimizing Arbitrage Opportunities in Automated Market Makers Using Scalable Blockchain Flash Loans

This paper delves into the innovative application of flash loans within decentralized finance (DeFi), specifically in automated market maker (AMM) models. These systems streamline trading and improve liquidity through algorithmic asset pricing. However, high transaction fees and network congestion hinder their scalability. This research proposes strategies to optimize gas fees and enhance scalability by incorporating dynamic gas pricing and efficient fee management. By leveraging both Ethereum and Polygon networks, the system adapts to network conditions and addresses throughput limitations. The paper underscores the benefits of flash loans, including increased liquidity, cost efficiency, and risk mitigation, which are essential for arbitrage opportunities. Ultimately, this work aims to strengthen the DeFi ecosystem by promoting more robust and efficient trading strategies, paving the way for future innovations and greater financial inclusivity. Furthermore, a mathematical analysis of transactions, including profit and loss differences, is conducted to compare traditional arbitrage methods with the proposed scalable and efficient AMM-based approach.