{"id":1824,"date":"2020-07-02T14:33:00","date_gmt":"2020-07-02T14:33:00","guid":{"rendered":"https:\/\/digiterrebestg.wpengine.com\/?p=1824"},"modified":"2024-05-30T09:19:44","modified_gmt":"2024-05-30T09:19:44","slug":"the-technology-behind-successful-algo-trading-implementation","status":"publish","type":"post","link":"https:\/\/www.digiterre.com\/us\/2020\/07\/02\/the-technology-behind-successful-algo-trading-implementation\/","title":{"rendered":"The Technology Behind Successful Algo Trading Implementation"},"content":{"rendered":"
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The Technology Behind Successful Algo Trading Implementation<\/h1>\n\n

At this time of major disruption for energy trading and technology teams, it can be challenging to allocate quality time to think more broadly about what\u2019s happening to markets, risk and operations \u2013 and consider the implications of the macro trends facing the industry, including digitalisation, automation, AI and algo trading. Luckily, that\u2019s exactly what I was able to do at Energy Trading Week, which took place over two days, entirely online of course, and I have since been reflecting about the content of the event.<\/p>\n \n <\/div>\n<\/section>\n\n\n

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What struck me the most about the conference were the discussions about algo trading.  The session on \u201cSecrets to a Successful algo Trading Implementation\u201d, featuring industry experts Alex Raguz, Head of Algorithmic Trading at ElbOil, and Erdem Sezer, Manager of Analysis and Trading Strategies at Aksa Enerji, was particularly thought-provoking.<\/p>\n\n\n\n

There was an interesting discussion on the benefits of algo trading, including hedging risk within revenue streams, the removal of human and emotional factors in trading, and the increased speed algo trading enables, and a firm consensus emerged that algo trading needs to be underpinned by an effective risk strategy.<\/p>\n\n\n\n

Both Erdem and Alex agreed that \u201cyou need a robust, well-structured IT infrastructure\u201d before embarking on algo trading while maintaining a healthy appetite for risk.  Critical issues to look out for include governance \u2013 who owns and makes decisions about infrastructure \u2013 and the assessment of on-premise versus cloud solutions \u2013 you can have a bit of both, with computation for analysis on cloud and execution in-house.<\/p>\n\n\n\n

It was also telling that the participants surveyed noted the \u201clack of good quality data\u201d as the top reason for not attempting algo trading. \u00a0Indeed, on several occasions, the panelists spoke about the importance of having clean data for reliable signals and the necessity of assessing the \u201cactual\u201d versus the \u201ctheoretical\u201d algorithmic performance and course-correcting accordingly.<\/p>\n\n\n\n

Much of the discussion centered around data.\u00a0Getting clean data is a crucial element of the secret behind performing effective algo trading and this marries up with our experience at Digiterre.\u00a0We have been helping energy trading companies establish a high quality \u201csingle version of the truth\u201d data stream, from multiple data sources, to derive insights from analytics, algorithmic and the robust governance and human oversight around these platforms.\u00a0These themes came up repeatedly during the panel session and the networking afterwards.\u00a0 It will be fascinating to see how they develop in the future.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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About the Author<\/h3>\n
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Digiterre<\/h4>\n\n \n \n <\/div> \n <\/div>\n
\n Date: 02\/07\/20<\/strong><\/span>\n Category: Industry Insights\/ Tech Insights<\/strong><\/span>\n <\/div>\n <\/div>\n<\/section>\n\n\n
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