Venue Message Rate Limits: Architecting a Multi-Venue Quoting Engine Around Exchange Throttling
How exchanges actually meter your order flow, why one rate limit across venues fails, and the governor architecture that holds the line.
HFT Tech Advisory
Senior technology executive in institutional electronic trading, 30+ years buy and sell side. Author of "C++ High Performance for Financial Systems," creator of VisualHFT. I cover exchange architecture, microstructure, and infrastructure that moves P&L.
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I Was Asked to Rebuild an HFT System in C#. I Laughed. Then I Measured It Twice.
C++ wins the FIX decoder by a third, until you hand-write ten lines of Vector256. Then I re-ran the whole matrix and my own headline died. Full harness, 869 raw launches, every retraction public.
The Order-to-Trade Ratio Has Four Readings. Most Desks Only Know One.
Venues price your order-to-trade ratio, two states tax it, enforcement reads it as intent, and Rule 605 now publishes it. One tape, four ledgers.
Multi-Venue Trading Architecture: The Four Layers Beneath Smart Order Routing
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Before, During, and After the Fill: A Practitioner's Map of Market Microstructure Measurement
Perold, Almgren-Chriss, VPIN, and the market microstructure research behind measuring execution before, during, and after the fill.
Level 3 Market Data in Crypto: Why Most Exchanges Still Withhold the Order Book's Full Depth
Level 3 market data exists inside every CLOB matching engine. Most crypto exchanges do not sell it. What that packaging gap costs and hides.
The Anatomy of a $50M Latency Build: Trading System Architecture Decisions That Separate a Machine From a Money Pit
Where quant fund infrastructure money burns: a $50M build anatomy, three architectural failures, and the instrument-first framework that prevents them.
What and How to Measure Trading System Latency: A P99 Acceptance Bar for Low Latency Infrastructure
The boundary, load condition, and percentile a real latency acceptance bar needs, with the OPRA proof and a five-minute check.
Designing Market Data for Deterministic Replay
A design guide to a market-data path you can replay deterministically: capture at the boundary, fix event order in the data, replay through the same binary, then prove the output matches.
Illiquid Market Making: When the Feature Pipeline, Not the Model, Determines Whether You Survive
Avellaneda-Stoikov fails on thin books. The fix is not the model — it is the feature pipeline between the book and the quote.