Neural Network Based Forecasting of Foreign Currency Exchange Rates
Journal Title: International Journal on Computer Science and Engineering - Year 2014, Vol 6, Issue 6
Abstract
The foreign currency exchange market is the highest and most liquid of the financial markets, with an estimated $1 trillion traded every day. Foreign exchange rates are the most important economic indices in the international financial markets. The prediction of them poses many theoretical and experimental challenges. This paper reports empirical proof that a neural network model is applicable to the prediction of foreign exchange rates. The exchange rates between Indian Rupee and four other major currencies, Pound Sterling, US Dollar, Euro and Japanese Yen are forecast by the trained neural networks. The neural network was trained by three different learning algorithms using historical data to find the suitable algorithm for prediction. The forecasting performance of the proposed system is evaluated using three statistical metrics and compared. The results presented here demonstrate that significantly close prediction can be made without extensive knowledge of market data.
Authors and Affiliations
S. Kumar Chandar , Dr. M. Sumathi , Dr S. N. Sivanandam
Keywords
Related Articles
- EP ID EP88697
- DOI -
- Views 403
- Downloads 0
Generating Membership Values And Fuzzy Association Rules From Numerical Data
The most important task in the design of fuzzy classification systems is to find a set of fuzzy rules from training data to deal with a specific classification problem. In this paper, a method to generate fuzzy rules fro...
Neuro Language Generator
‘Neuro Language Generator using Finite State Machine’ is based on neural network and finite state machine. The undamental properties of neural network along with the power of Turing machine prove how it can be implement...
A Modified Robust Queue Management with Feedback Compensation Technique to Manage the Congestion Control in Wireless Communication Networks
At present there has been a tremendous growth in the computer networks and wireless networks. Due to the enormous growth of voice, audio, video and data applications over the wireless networks, the requirement of congest...
BER Analysis to Increase Capacity of A Cellular System Using SDMA Over a Multipath Rayleigh Fading Channel
In this paper, we have presented how the capacity of cellular system can be enhanced by using Space Division Multiple Access (SDMA) with directive antenna in mobile communication systems. One of the biggest draw back of...
A Study of Image Segmentation and Edge Detection Techniques
Image segmentation is the key behind image understanding. Image segmentation is one of the most important steps leading to the analysis of processed image data. It is the prime area of research in computer vision. A numb...