Nicholas Pratt
Nicholas Pratt

Achieving more rapid Algorithmic FX trade strategy development

Time is money and nowhere can this truism be taken more literally than in the trading world. Algorithmic trading in FX has grown in order to sate the appetite for higher frequency, larger volume trading and more sophisticated strategies – all of which can be more easily achieved through the deployment of automated systems.

But during its development over the last five years and the intense marketing efforts that have accompanied it, the algorithmic trading industry and its associated applications have often been unfavourably likened to an arms race, where participants are busy racing each other to some kind of finite end-goal where the trades cannot get any faster, the latency cannot get any lower and real-time cannot get any more, well, real.  So with this in mind, is it still possible to speed up the deployment of algorithmic trading applications? What technology is available to help reduce the time to market for newly created algorithms? Can the testing process be successfully preserved in the rush to deploy new algorithms? Similarly, can algorithms be more efficiently and accurately modified in order to capture market changes – particularly in a volatile market like FX? Or are we entering an era of disposable algorithms where they have only a limited shelf-life and are quickly despatched to some sort of cyber...continued

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