Forecast Forex With ANN using fundamental data

Ming Hao Eng, Yang Li, Qing Guo Wang, Tong Heng Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Citations (Scopus)

Abstract

An effective foreign exchange (Forex) trading decision is usually dependent on effective forex forecasting. This paper reports empirical evidence that an artificial neural network (ANN) is applicable to the prediction of foreign exchange rates. The architecture of the network and the related algorithms are described. The effects of the choice of inputs into a neural network model are examined. Except for the normally used time series data and technical indicators, fundamental indicators such as interest rates and gross domestic products are fed into the neural networks to see if any relationship may be captured and improve the predictive capabilities of the model.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2008
Pages279-282
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventInternational Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2008 - Taipei, Taiwan, Province of China
Duration: 19 Dec 200821 Dec 2008

Publication series

NameProceedings of the International Conference on Information ManagementProceedings of the International Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2008
Volume1

Conference

ConferenceInternational Conference on Information Management, Innovation Management and Industrial Engineering, ICIII 2008
Country/TerritoryTaiwan, Province of China
CityTaipei
Period19/12/0821/12/08

Keywords

  • Artificial neural network
  • Foreign exchange rate
  • Fundamental economic data

ASJC Scopus subject areas

  • Information Systems and Management
  • Industrial and Manufacturing Engineering

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