This guide is for engineers who do not have a background in finance or economics but want to understand how to build blockchain technology that allows for more parties to be economically empowered.
'MEV', or maximal extractable value, from the view of a blockchain infrastructure or application developer, can be conceptualized as the way which entities are able to extract value from the underlying system. This list is heavy on market making strategy and algorithmic/model based trading topics as the behaviors in traditional finance are being copied in decentralized finance in an extractive manner. Different from traditional finance, blockchains are not able to regulate entities via law into 'good' behavior and instead must rely on architecture, permissions, and incentive structures to enable the intended users to benefit from a system.
The resources in the list build on each other if consumed in order.
Traditional finance starting using computers to trade in the 1960s. Blockchains are different in their architecture and permissions, but still deal with pools of assets that people are interested in trading. Understanding the basics of traditional finance, particularly how entities are allowed to interact with each other, is useful as blockchains are creating an alternative system.
These recommendations are meant to be accessible to people who have little exposure to finance.
- Flash Boys by Michael Lewis
- Famous for sensationalizing front-running and for claiming that traditional markets are 'rigged'. Is an odd/controversial read because the book better describes what is happening in blockchain trading than in traditional finance (there is no front-running in traditional finance). Recommended reading because it does a good job of introducing why speed of information matters and is referenced often in other works.
- Complex Systems Season 1 Episode 1: How the Smart Money teaches trading with Ricki Heicklen
- Ricki Heicklen (ex Jane Street) discusses how she teaches people to be algorithmic traders. Good to listen to understand how order book trading works from the perspective of a trader. Touches on adverse selection, why it's better to clear orders often, the power of knowing the identities of participants, the difficulty of position sizing, and the different types of arbitrage.
- Acquired Season 14 Episode 3: Renaissance Technologies
- Complete history of Renaissance Technologies. Goes over the history of model-based trading and why being right 51% of the time will make you billions. Helpful to understand how to build bots (introduced in the Complex Systems episode) and how the statistical games discussed in the the MEV-SBC'24 recording are centralizing.
- Flash Boys : Not So Fast: An Insider's Perspective on High-Frequency Trading by Peter Kováč
- Response book to Flash Boys, goes over why traditional finance does not suffer from front-running or other MEV games (hint: regulation). Good to read to understand how unregulated blockchain trading is and to understand how market makers operate on a business level. Needed read for the more advance traditional finance recommendations.
- Flash Boys 2.0: Frontrunning, Transaction Reordering, and Consensus Instability in Decentralized Exchanges by Philip Daian Et al.
- Lays out how MEV games are played on blockchains in an explicit manner.
- Sorella Lab's Brontes MEV Dashboard
- Shows real time estimates of how much MEV revenue/profit is being extracted per Ethereum L1 block. Divides MEV activies between CEX-DEX, sandwich, atomic arbitrage, JIT sandwhich, and JIT. More about their methodology can be found in their docs.
- Interview with a Block Builder (Kubi from Titan)
- Discusses how Ethereum block builders use vanilla mempool flow, searcher bundle flow, private transaction flow, and exclusive transaction flow to build blocks containing the value shown by the Brontes dashboard.
- FlashBots MEV-SBC’24 Recording: Max Resnick & Phil Daian The Incentives of Short Term Censorship Resistance.
- Lays out how blockchain architecture affects how economic powerhouses are able to extract value. Main takeaway is that economic powerhouses (builders/searchers) will try to make money either through latency games, spamming games, or auctions. Blockchain architectures must choose which game they expose. Posits that the four properties needed for a decentralized cryptocurrency include: permissionlessness (ability to join system and express economic value at any time), logical and technical distribution across many nodes, geographic distribution to minimize colocation profit, and the ability for neutral builders to enter the market without substantial barriers.
- i'M NeW t0 mEv by @mteamisloading
- Culture and technical piece on 'how to be a searcher'. Good starting point if you want to investigate searching with sections like 'Bot best practices' and 'Social Norms For Searchers'.
- Advances in Financial Machine Learning by Marco Lopez de Prado.
- Introduction to financial machine learning. This book was super helpful (for an engineer with no data and/or ML background) to understand the different steps involved in using machine learning for aiding in investing. I'm only 1/2 way through, will finish the blurb once done.
- Market Maker Inventories and Stock Prices
- Automated market maker inventory management with deep reinforcement learning
- High-frequency trading in a limit order book
- The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response
- Who Wins Ethereum Block Building Auctions and Why? by Burak Öz
- Illuminating Ethereum's Order Flow Landscape
- DeFi Reading List
- Jump Crypto Reading List
- MEV Weekend Reading List
- Comprehensive guide to the Defi Derivative landscape
Reach out if you have more resources, twitter: @lobstermindset! Will update as I find more relevant material.