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Cracking the Myths of Big Data Forecasting

Xuxin Mao, UCL

Date Icon Week 6, Wednesday 22 February HT 2017
Time Icon 7:00pm
Location Icon Exeter College

Amid recent economic and political uncertainties, it is the worst of times and it is also the best of times for forecasters. While few have foreseen economic recessions or political populism, robust predictions have become high sought-after treasures that everyone is determined to possess.

Dr Xuxin Mao (UCL) will illustrate how to use his Topic Retrieved, Uncovered and Structurally Tested (TRUST) platform to generate real-time robust forecasting capability. The TRUST platform incorporates the recent developments in behavioural science, Big Data analytics, AI-based data mining, and structurally econometric modelling to analyse both traditional data and Big Data from various resources like newspapers, Google, Wikipedia, Tweets, etc.

Dr Mao will present with examples on how to use the innovative toolkits to analyse and predict human behaviour in social and business contexts. The first group of examples involve his recent political predictions, such as the 2014 Scottish Referendum, the 2015 UK General Election, the 2016 UK local elections, the 2016 EU referendum, and the 2016 US election. The second group of examples are about the recent applications in business analytics and predictions, including predicting house prices, construction profit margin for ONS, and life insurance demand for Groupama. Dr Mao will also present suggestions for further research and wider applications, which will be followed by a Q&A.

The event is free. Please register your interest here.

Dr Xuxin Mao(毛旭新)is an economics lecturer at UCL, and researcher in application of AI and Big Data analytics, associated with ONS, Invennt and L’Institut Europlace de Finance. For the past years, he studied economics, finance and mathematics in China Denmark, France, Germany and the UK, and worked across industries and countries as UNHCR volunteer, academic researcher, certified Financial Risk Manager (FRM), investment banker, and Big Data forecaster. More details can be be found on his personal webpage.