Designing Financial Market Intelligent Monitoring System Based On OWA BENJAMIN FONOONI, SEIED JAVAD MOUSAVI MOGHADAM Artificial Intelligence Alternative Solutions Lab, Tehran IRAN Abstract: The need for intelligent monitoring systems for financial markets especially Foreign Exchange has become a necessity to keep track of this market. Financial markets conform to some mathematical concepts and cause it to be analyzed with different Artificial Intelligence (AI) algorithms. Data Fusion has been applied in different fields and the corresponding applications utilize numerous mathematical tools. This paper headed for applying Ordered Weighted Averaging (OWA) operator in order to support trading decisions based on technical analysis in Foreign Exchange Market. Key-Words: Decision Making, Data Fusion, OWA, Computational Finance, Financial Markets Analysis, Foreign Exchange 1 Introduction Technical analysis has been a part of financial practice for many decades. It attempts to understand the emotions in the market by studying the market itself, as opposed to its components and assumes that certain chart formations can indicate market psychology about either an individual stock or the market as a whole at key points. It is suggested by several academic studies that technical analysis may well be an effective means for extracting useful information from market prices [2]. Technical analysis is widely used among traders and financial professionals, and some studies say its use is more widespread than is fundamental analysis in the foreign exchange market [5], [12]. Technical analysts identify non-random price patterns and trends in financial markets and attempt to exploit those patterns [11] by using various methods and tools. Technicians especially search for archetypal patterns, such as head and shoulders, and also study such indicators as price, volume, and moving averages of the price. They use judgment gained from experience to decide which pattern a particular instrument reflects at a given time, and what the interpretation of that pattern should be. A trader has in mind the task of developing a trading system that optimizes some profit criterion, the simplest being the total return. A trading system is governed by a set of rules that do not deviate based on anything other than market action. The system operate within the parameters known by the trader comes from tools and indicators. The parameters can be trusted based on historical analysis and real world market studies, so that the trader who is familiar with the trading strategy and its operating characteristics can have confidence in a pre- determined trading strategy. A trading strategy can automate all or part of investment portfolio. Computer trading models can be adjusted for either conservative or aggressive trading styles. The proposed algorithm formed based on the fact that all technical analysts fuse information to determine next market trend. Data fusion is the process of combining data or information to estimate or predict entity states and involves combining data in the broadest sense to estimate or predict the state of some aspect of the universe. Often the objective is to estimate or predict the physical state of entities including their identity, attributes, activity, location, and motion over some past, current, or future time period [10]. This project utilizes data fusion concepts in order to help technical analysts make better trading decisions by integrating information perceived from current market state involving some indicators values and price patterns. The use of data fusion in Forex Market would be integrating data and knowledge from different indicators and price patterns with the aim of maximizing the useful information. It improves reliability or discriminant capability while offering the opportunity to minimize the data retained. 2 Overview on OWA Data Fusion is the process of combining data and APPLIED COMPUTING CONFERENCE (ACC '08), Istanbul, Turkey, May 27-30, 2008. ISBN: 978-960-6766-67-1 35 ISSN: 1790-2769