Web Browser-Based Forecasting of Economic Time-Series

TitleWeb Browser-Based Forecasting of Economic Time-Series
Publication TypeConference Paper
Year of Publication2016
AuthorsRivas, V. M., Parras-Gutiérrez E., Merelo J. J., Arenas M. G., and García-Fernández P.
EditorBucciarelli, Edgardo, Silvestri Marcello, and González Sara Rodríguez
Conference NameDecision Economics, In Commemoration of the Birth Centennial of Herbert A. Simon 1916-2016 (Nobel Prize in Economics 1978)
PublisherSpringer International Publishing
Conference LocationCham
ISBN Number978-3-319-40111-9

This paper presents the implementation of a time series forecasting algorithm, jsEvRBF, that uses genetic algorithm and neural nets in a way that can be run in must modern web browsers. Using browsers to run forecasting algorithms is a challenge, since language support and performance varies across implementations of the JavaScript virtual machine and vendor. However, their use will provide a boost in the number of platforms available for scientists. jsEvRBF is written in JavaScript, so that it can be easily delivered to and executed by any device containing a web-browser just accessing an URL. The experiments show the results yielded by the algorithm over a data set related to currencies exchange. Best results achieved can be effectively compared against previous results in literature, though robustness of the new algorithm has to be improved.