A limit order is a peculiar kind of promise. You tell the market “I’ll trade with you but only at this price or better.” That sounds like control. But the market can decide when that promise becomes attractive. If new information arrives before your order executes, your price may suddenly become exactly where you don’t want to trade. This creates a subtle asymmetry. A market order gives up price control to gain execution certainty. A limit order gives up execution certainty to gain price control. Neither is simply “better.” They exchange one kind of certainty for another. That distinction explains something traders often experience Getting filled can itself be information. Your order didn’t merely participate in the market. The market chose to interact with you. And sometimes the reason you got the fill is precisely the reason you should have been more cautious. #MarketMicrostructure# #Trading# #Execution#

The mechanics and complexities of futures expirations, and how HFTs and market makers handle them from a technical perspective. • A single futures contract is associated with more than one expiration-related date. Physically settled contracts in particular have first notice dates, last trading dates, last notice dates, last delivery dates, final settlement dates, and exchange-defined “roll dates” that may be none of the above. The underlying asset type determines which dates are most relevant for tracking expiration effects. In addition, an exchange’s current trade date is not necessarily the calendar date. For example, CME advances the trade date to the next business day at 16:00 CT. HFTs maintain accurate metadata including all relevant expiration dates by building proprietary symbology databases. Firms reconcile across multiple input sources including real-time binary-encoded symbol definitions from live market data feeds, daily universe files from FTP, and third-party normalization services such as Bloomberg and FactSet. • The official front month is not necessarily the most-traded front month. Volume and open interest routinely migrate days to weeks ahead of last trade date or first notice date. For example, Treasury futures roll most open interest in the last 10 business days before the delivery month starts. Liquidity rolls in energy and agricultural products are determined by commercial hedging and index fund activity. Market makers decide which futures contracts to reference based on empirical liquidity measurements. Live and historical market data capture services are essential for tracking when the market decides to shift to the next expiry. • ETFs with futures holdings will convert front month positions to back month positions gradually over a predefined roll period. Arbitrage market-making systems that accurately price the fair value of futures-based funds need to reference multiple contract expiries in the right quantities based on the trading day. The indexes used to settle commodity perpetual futures use a similar liquidity rolling strategy. ETF market makers download basket definition files directly from issuers and encode the roll mechanics from prospectuses to ensure the fund holdings are modeled correctly. Sometimes the issuers publish mistakes in their own basket files, providing an additional source of edge for participants savvy enough to catch them. • Efficiently trading out of front month futures positions and legging into the next expiry requires an understanding of market microstructure. Trading firms time execution to the optimal combination of order book depth and spread tightness in the front month contract, back month contract, and atomic calendar spread if supported by the exchange. HFTs build models that predict calendar roll prices and spreads as a function of time-to-expiry. Firms also deploy algorithms that gradually execute roll strategies while minimizing alpha leakage. Some firms will pre-position ahead of the liquidity roll based on known positions of large funds in order to take advantage of the expected flow. • Most futures brokerages automatically roll or liquidate positions to avoid expiry, especially in the case of physically settled commodity futures. The specific date used as the deadline depends on the clearing firm, with first notice and last trade the two most common cutoffs. Auto-liquidations incur extra fees and often result in large amounts of slippage from inefficient execution. The solution for HFTs is to become direct members of futures exchanges and avoid any intermediation by third-party clearing firms or brokerages. In place of external processes, the internal back-office teams at HFTs and market makers build monitoring tools to ensure futures trading desks do not unintentionally take positions to expiry or delivery. Exchange membership is prohibitively costly and time-consuming for non-HFT market participants. Solving the above issues with futures expirations has become a hard-won source of edge for many HFTs and market makers. While perpetual futures reduce complexity and deadweight cost, they also remove profit opportunities for trading firms and fee capture for exchanges, which is an under-discussed source of the current pushback against listing commodity perpetuals in the US.

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Expect more English in my posts going forward. The logic is simple: Crypto is a global playing field. The core infra updates, raw API specs, and serious discussions on market microstructure—the primary sources are almost always in English. Code and markets speak the same language.

First Principles Ep. 5 with Paul Milgrom One of the most important auction designs in modern history was sold to the FCC on a 3.5-inch disk. Nobel Prize winner Paul Milgrom on auctions, price discovery, and how mechanism design became real-world infrastructure — from spectrum auctions to DeFi. Hosted by @Tim_Roughgarden with @skominers. 00:00 Intro: economics assumptions that are “just wrong” 02:19 Scott Kominers and Tim Roughgarden on the genius of Paul Milgrom 05:35 An intro to the  Glosten-Milgrom model: The paper that created entire fields of economics 07:48 The auction theory breakthroughs of the 1980s 17:15 Why market microstructure matters for DeFi 24:17 When math teaches economics something new 32:38 How theory became spectrum auction design 36:22 The floppy disk that helped convince the FCC 41:05 What changed when auctions moved online 45:28 The auction that reorganized television 1:07:30 What economics and computer science can learn from each other 1:13:22 Futures markets for compute 1:15:12 Paul Milgrom’s advice for builders