Master's Thesis Deniz Yüksel

A Retrospective Analysis of Public and Private Order Flow on the Ethereum Blockchain

Abstract

Lately, transacting publicly on Ethereum blockchain has become riskier due to increased incentives of profit-seeking actors. One of the major risks is getting front-run by a profit-seeking bot that aims to observe the public order flow and extract value out of the original transaction, rendering the public order flow disadvantageous for the user. In response to these externalities users face, organizations such as Flashbots developed private RPC endpoints to offer users front-running protection. By applying a configuration to their wallets, user transactions can bypass the public order flow – preventing profit-seeking bots to detect the transaction and extract profits.

While using private RPC endpoints bring front-running protection, it also renders the market inefficient by delaying to the next block, any economic operations to be executed on the state created – known as back-running. These neutral operations towards the user transaction are also a way of generating profits for profit-seeking actors. This demand led to the emergence of Order Flow Auctions (OFAs), an auction conducted in private order flow for MEV-searchers to bid for back-running a user transaction. This design protects the user from getting front-run while also enabling the user to sell their opportunity to be back-run.

In this thesis, we will examine the evolution of private order flow, bypassing the peer-to-peer public order flow and going into the Ethereum blockchain. To that extent, we will conduct a historical examination of the public and private order flow volume. Moreover, we will delve into identifying sources of private order flow and study OFAs as a prominent solution. Considering the current technological landscape, we will develop a taxonomy for OFAs regarding their implementations, benefits, and target users. Subsequently, we will conduct a detailed examination of the historical changes in public/private memory pool transaction volumes, identify the possible factors influencing these changes, and analyze the evolution of private memory pool usage from the user perspective. Consequently, we will assess the negative impacts of the rise in private transaction volume on public memory pool users by means of gas prices and inclusion times.

• RQ01:
  
  • What are the risks of submitting transactions to the public mempool of the Ethereum blockchain?
    • What solutions are available to mitigate these risks?
    • Can a taxonomy be built to classify these solutions?
• RQ02: 
  • How did the public memory pool usage change over time, and what factors affected this change?
    • How prominent was Flashbots’ private endpoint in the pre-merge era?
    • What is the source of the private order flow in post-merge Ethereum?  
• RQ03:
  • How successful are the OFAs in returning their values to users?
  • How much percentage of the value is redistributed back to transaction originators?
• RQ04:
  • What is the impact of increased usage of private endpoints on the users that transact publicly?