Journal of Computer Science

EVENT-DRIVEN BUSINESS INTELLIGENCE APPROACH FOR REAL-TIME INTEGRATION OF TECHNICAL AND FUNDAMENTAL ANALYSIS IN FOREX MARKET

Mohammed AbuHamad, Masnizah Mohd and Juhana Salim

DOI : 10.3844/jcssp.2013.488.499

Journal of Computer Science

Volume 9, Issue 4

Pages 488-499

Abstract

Forex market is the most liquid financial market and the largest market in the world. Forex market has been analysed using two isolated approaches, technical analysis and fundamental analysis. Technical analysis attempts to predict the movement of prices by studying the historical data of the market whereas fundamental analysis concerns essentially with the overall state of the economy. Relying on one kind of analysis limits the quality of trading decisions therefore traders usually gain insight into the market by analysing many factors which may influence the market state and the price movement. This process has become increasingly challenging due to the vast and variant number of prices’ determinants and the rapid changes in the market dynamics. This study proposes an event-driven business intelligence approach to respond immediately to any change in the market status by generating trading signals based on different analyses. Targeting the value associated with the data as it arrives, different models are built to capture and process the data of three currencies against US dollar in different frequency as well as the data of nine US macroeconomic indicators. The time-series data for both technical and fundamental indicators are modelled using artificial neural network while a knowledge base model is implemented to integrate the signals generated by time-series models. The experimental results show a remarkable improvement in the quality of trading signals using real-time consideration of different analyses.

Copyright

© 2013 Mohammed AbuHamad, Masnizah Mohd and Juhana Salim. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.