ethrd

1/ 🚀 Just published a deep dive on Cross-Chain MEV Auctions! 🌐🔍 In this article, I explore how to model and analyze separate vs. joint auctions to maximize proposer revenues in a multi-chain MEV world. 📈✨ [Read here](https://thogiti.github.io/2024/06/03/Cross-Chain-MEV-Auction-Modeling.html)

2/ 🔍 The base model by Ed Felten from Arbitrum serves as the baseline. It breaks down the basics of separate and joint MEV auctions, helping us understand the mechanics and broader implications in a multi-chain environment. (https://research.arbitrum.io/t/do-shared-mev-auctions-actually-increase-revenue/9606)

3/ 📊 Next, I expand the model to include bidders risk aversion and preferences. Understanding the risk preferences is crucial to predicting how bidders act under uncertainty, affecting proposer revenue outcomes in separate and joint auctions.

5/ 🔗 Finally, I explore combinatorial auctions where bidders place bids on predefined combinations of chains. This approach captures synergies between chains, allowing for more efficient and effective auction mechanisms, maximizing proposer revenue.

6/ ✨ By combining these models—risk aversion, dynamic auctions, and combinatorial auctions—we gain a comprehensive understanding of how to optimize MEV auctions in a multi-chain world. Dive deeper into the analysis here: [Read more](https://thogiti.github.io/2024/06/03/Cross-Chain-MEV-Auction-Modeling.html)

4/ 🔄 Dynamic auctions are also explored. In sequential auctions, bidders adjust their strategies based on earlier results, which reflects real-life scenarios and impacts overall revenues. This model provides insights into how bidder behavior evolves over time.