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Bar the LSE’s recent mishap, trading systems are getting astoundingly fast. Over the last few years the race to develop the fastest systems, with the most streamlined and slick infrastructure has intensified greatly.
The increasing necessity to cater for black box traders and the clutch of new trading platforms that are coming online as a result of MiFID, has only intensified the pace race in trading. The LSE’s Tradelect platform (when working), for example, is able to make over 3000 trades a second.
The non-stop drive to trade as fast as possible has implications on both sides of the fence. The faster you are the more competitive you can be. As such both trading platforms and trading houses need to make sure they have the technology in place to both keep up with and take advantage of super trading speeds. This ‘hyper-trading’ combined with the current nervous market can also create a recipe for great success and monumental failure all within a minute timeframe.
An area where this race has had a profound effect is the development of trading software. As the trading environment changes so software development has to adapt. Developing trading systems using the traditional ‘waterfall’ approach simply takes too long leaving systems and algorithms out of date by go-live. Agile development on the other hand is much better suited, creating software in short iterations.
With quick feedback cycles, extra client involvement and development iterations of two to three weeks, the finished software will always be completely up-to-date with the latest algorithms, compliance information and so on. By using agile development for new trading systems, traders can ensure their systems can take anything that the trading world throws at them.
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Leon Fischer-Brocks Co-Founder | CEO at Bloxley
22 May
Priyanka Rao Content Strategist at Jupiter Money
Vijay Mayadas President, Capital Markets at Broadridge
19 May
Erica Andersen Marketing at smartR AI
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