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Forecasting foreign exchange rates using neural networks

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Date Issued:
2000
Summary:
Time series is a phenomena which appears in the financial world in various forms. One of the objectives of time series is to forecast the future based on the past. The goal of this thesis is to use foreign exchange time series, and predict its future values and trends using neural networks. The thesis covers background work in this area and discusses the results obtained by other researchers. A neural network is then developed to predict the future values of the USD/GBP and USD/DEM exchange rates. Both single-step and iterated multi-step predictions are considered. The performance of neural networks strongly depends on the inputs supplied. The effect of the changes in the number of inputs is also considered, and a method suggested for deciding on the optimum number. The forecasting of foreign exchange rates is a challenge because of the dynamic nature of the FOREX market and its dependencies on world events. The tool used for building the neural network and validating the approach is "Brainmaker".
Title: Forecasting foreign exchange rates using neural networks.
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Name(s): Talati, Amit H.
Florida Atlantic University, Degree grantor
Pandya, Abhijit S., Thesis advisor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2000
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 116 p.
Language(s): English
Summary: Time series is a phenomena which appears in the financial world in various forms. One of the objectives of time series is to forecast the future based on the past. The goal of this thesis is to use foreign exchange time series, and predict its future values and trends using neural networks. The thesis covers background work in this area and discusses the results obtained by other researchers. A neural network is then developed to predict the future values of the USD/GBP and USD/DEM exchange rates. Both single-step and iterated multi-step predictions are considered. The performance of neural networks strongly depends on the inputs supplied. The effect of the changes in the number of inputs is also considered, and a method suggested for deciding on the optimum number. The forecasting of foreign exchange rates is a challenge because of the dynamic nature of the FOREX market and its dependencies on world events. The tool used for building the neural network and validating the approach is "Brainmaker".
Identifier: 9780599813908 (isbn), 12699 (digitool), FADT12699 (IID), fau:9581 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 2000.
Subject(s): Foreign exchange rates--Mathmematical models
Foreign exchange--Forecasting--Mathematical models
Neural networks (Computer science)
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/12699
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.