There are other headlines which hit and filled our social media this week with an even more immediate impact. Theresa May set forth her Brexit deal to her cabinet. Within seconds of her cabinet leaving the five hour discussion there was noise on Twitter of resignations, moments later the first resignation had come in from Dominic Raab with his letter being openly posted on his own social media account. As the day unfolded Sterling continued to weaken with page views, mentions and likes undoubtedly being used as a form of forecasting tool. Likes and views can be tracked for user sentiment on a real time basis and it has been proven to show a directionally proportional performance on a market, with negative words and sentiments having a bearish effect.


In August 2017 Amazon’s stock price showed the amount of power negative sentiment can have by dropping 1.2% after a Tweet President Trump made. Although Jeff Bezos’ company recovered that same day, opinion has never before held such a reactionary power. Companies such as Toyota and Boeing have also suffered from very similar situations. It is a result of this that tools such as the Twitter Hedge Fund have emerged, whose emergence derives from their ability to evaluate information on social media for the benefit of companies, as the volume of data which flows through these platforms is immense.


In the commodity trading arena, information flowing through these platforms about factors such as weather conditions, agricultural diseases and supply of oil directly influences trading decisions. This data is now often found on social media before there is a change in the price of commodities and as such pre-determining the rise or fall of the price of a commodity that you are trading. The luxury of time has been lost. The importance of the freshness of data when ignored can of course lead to erroneous decisions. At the speed of which ‘new’ information now becomes available, it quickly becomes stale and loses its relevance. With this in mind, commodities largely derived from economies of either a developing or volatile nature with laborious monitoring systems is the new target for tech platforms such as Nowcast. The still prevalent several day delays in the publication of their statistics will become a thing of the past due to the information hungry nature of commodity trading firms. Even the most challenging of commodities will, in the future, be as reactive as a company’s stock.


Looking even further ahead, the job of a trader could in large turn to into a role fulfilled largely by artificial intelligence. As commodity companies come under further pressure to make profits, the demand to seek efficiencies through enhanced automation will become ever more prevalent. As to how far in the future this is, or to what extent a robot could fulfil this role is a topic for further debate.


Lauren Judd E: lauren.judd@adm.com T: +44 1322 444 820


13 | ADMISI - The Ghost In The Machine | November/December 2018


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