Forecasting currency exchange rates with an artificial bee colony-optimized neural network

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Publication Details

Author list: Worasucheep C.

Publisher: Hindawi

Publication year: 2015

Start page: 3319

End page: 3326

Number of pages: 8

ISBN: 9781479974924

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963621603&doi=10.1109%2fCEC.2015.7257305&partnerID=40&md5=f762ec52c6cd3125ea15ce07f118e454

Languages: English-Great Britain (EN-GB)

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Abstract

This paper applies a recent variant of Artificial Bee Colony (ABC) to optimize the weights of a three-layer feedforward neural network for forecasting of currency exchange rates of USD/EUR and USD/Yen. The inputs to the network is built from historical prices and a set of well-known technical indicators, including Moving Average, Moving Average Convergence/Divergence and Relative Strength Index. The forecasting model becomes a complex minimization problem with fifty-decision variables, many of which are interdependent. The ABC variant in this work is ABCDE that is a hybrid algorithm of original ABC with two different mutation strategies of Differential Evolution (DE). The experimental results present a superior performance of ABCDE in terms of both training and testing errors against original ABC, Back Propagation and ODE [35], an efficient variant of DE. ฉ 2015 IEEE.

Keywords

Forecasting, Foreign exchange rate