Chemical reaction optimisation: a hybrid technique applied to functional link artificial neural networks with least mean square learning for foreign exchange rates forecasting
by Kishore Kumar Sahu; Soumya Ranjan Sahu; Gyana Ranjan Biswal; Prabin Kumar Sahu; Himansu Sekhar Behera
International Journal of Swarm Intelligence (IJSI), Vol. 2, No. 2/3/4, 2016

Abstract: Forecasting foreign exchange rates has long been an important issue in international finance. Most of the standard econometric methods are unable to produce significant superior forecasts because of its built-in complexity and practical applications. Taking into consideration the worldwide financial capital market, the foreign exchange (FOREX) market has a very crucial role to play. Due to the globalisation of fiscal investment, the investors are interested to learn the co-movement of foreign exchange, so as to make their investments safe and earn profits in return. In this work, an improved ANN model is being proposed that hybridises chemical reaction optimisation with functional link artificial neural network for prediction of foreign exchange (FOREX) rate. Experimental result shows that the proposed model with least mean square (LMS) training outperforms other methods, which ultimately indicates that the proposed model can be an effective way to improve forecasting accuracy achieved by other counterparts.

Online publication date: Sat, 24-Dec-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Swarm Intelligence (IJSI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com