alexa ANN-Based Forecasting of Foreign Currency Exchange Rates
Business & Management

Business & Management

Journal of Stock & Forex Trading

Author(s): Joarder Kamruzzaman, Ruhul A Sarker

Abstract Share this page

In this paper, we have investigated artificial neural networks based prediction modeling of foreign currency rates using three learning algorithms, namely, Standard Backpropagation (SBP), Scaled Conjugate Gradient (SCG) and Backpropagation with Bayesian Regularization (BPR). The models were trained from historical data using five technical indicators to predict six currency rates against Australian dollar. The forecasting performance of the models was evaluated using a number of widely used statistical metrics and compared. Results show that significantly close prediction can be made using simple technical indicators without extensive knowledge of market data. Among the three models, SCG based model outperforms other models when measured on two commonly used metrics and attains comparable results with BPR based model on other three metrics. The effect of network architecture on the performance of the forecasting model is also presented. Future research direction outlining further improvement of the model is discussed.

  • To read the full article Visit
  • Open Access
This article was published in Letters and Reviews and referenced in Journal of Stock & Forex Trading

Relevant Expert PPTs

Relevant Speaker PPTs

Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version