Forecasting the 2015 General Election with Internet Big Data: An Application of the TRUST Framework

Many variables, such as currencies, are very difficult to predict and often researchers demonstrate that a simple random walk process can out-perform a model-based forecast using fundamentals. However, there is increasing evidence that such results can be overturned with the use of rich enough dynamic processes in the underlying statistical modelling and also by ensuring that a rich enough information set is used. Elections have also become increasingly difficult to predict, despite the use of increasingly sophisticated methods, with the 2015 UK General Election being a good case in point. In this paper we demonstrate that the kind of statistical methods used to predict currencies and other financial variables, combined with information culled from internet sources such as Google trends, can greatly improve on the predictions based solely on opinion polls. This paper offers the first real time test of the so-called Big Data for the UK 2015 General Election. Our real time predictions of both the overall UK and Scottish components of the election are very close to the actual outcomes. 1 Adam Smith Business School, University of Glasgow, Glasgow, G12 8QQ, Email: [email protected] 2 The Bartlett, University College London and AECOM, London, WC1E 6BT, Email: [email protected]