19April 2023By Denis Imaev, Managing Director, Head of Algorithmic Trading Development, Cantor FitzgeraldThe accelerated automatization of entire industries leaves no technological and procedural stone unturned, and trading is no different. The sheer number of fintech companies addressing various needs is the evidence. This is where the traditional emphasis on highly regulated middlemen, controlled risks, and tried-and-true legacy processes clashes, having to deal with growing amounts of data and the necessity to scale, embrace new products, and conquer new markets while reducing costs. These rapid changes present a unique set of challenges to automated trading systems designers. Sure, the environment of constantly shifting requirements is very familiar to us, but how do we deal with this "business as usual" and still build robust, adaptive, and cost-effective systems? And how can we make our offering stand out among a vast variety of competing products?Mind the edge conditionsData-driven software often relies on models that best describe "average" scenarios, additionally constrained by various simplifying assumptions. Real-world cases however rarely fall into some generic category, and electronic trading with its asynchronous and unstable Denis ImaevENGINEERING TRADING SYSTEMS-- CHALLENGES AND OPPORTUNITIESINSIGHTSCXO
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