Proof Engineering: The Algorithmic Trading Platform

This is a semi-technical post about how we built an institutional-grade algorithmic trading platform from scratch in the cloud. As much as we want to, we cannot possibly include all of the details in a single post, so this is more of a high-level post, and future posts will talk about the individual topics in more technical depth.

Why Build It? A High-Performance Trading System in the Cloud The Equities Ecosystem Cloud Selection (Our Choice: AWS) Extranet (Our Choice: TNS) Market Data (Our Choice: Exegy) System Architecture The Tech Stack High Performance Java Cloud Setup and InfoSec The OMS and the Algo Engine FIX Gateways User Experience Infrastructure and DevOps Backoffice Closing Thoughts

“Finance is a bloated industry” — is the first line on our website. At least part of the premise of Proof is that we know this industry really well, and we know where the excesses and conflicts-of-interests lie, and we should be able to methodically build a leaner version of an equities agency broker that employs all of the tools and tricks that it needs to, but none that it need not. Our intention is to start very simple and add on complexity (and thereby, cost) as it is proven to be needed through rigorous research and/or analysis (e.g. what are the scenarios where depth-of-book market data adds to the trading performance? ok, now let’s prove that answer rigorously!). For us, we needed to be the architects of our minimalist vision in a very direct way.

If we had licensed or partnered with an existing or off-the-shelf platform, no matter how flexible, we’d have been constrained in the solutions that we can dream up by an external system that we don’t fully understand.

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