Journal
NEURAL COMPUTING & APPLICATIONS
Volume 19, Issue 8, Pages 1165-1195Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-010-0362-z
Keywords
Artificial neural networks; Expert system; Hybrid intelligent systems; Credit evaluation; Portfolio management; Financial prediction and planning
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Nowadays, many current real financial applications have nonlinear and uncertain behaviors which change across the time. Therefore, the need to solve highly nonlinear, time variant problems has been growing rapidly. These problems along with other problems of traditional models caused growing interest in artificial intelligent techniques. In this paper, comparative research review of three famous artificial intelligence techniques, i.e., artificial neural networks, expert systems and hybrid intelligence systems, in financial market has been done. A financial market also has been categorized on three domains: credit evaluation, portfolio management and financial prediction and planning. For each technique, most famous and especially recent researches have been discussed in comparative aspect. Results show that accuracy of these artificial intelligent methods is superior to that of traditional statistical methods in dealing with financial problems, especially regarding nonlinear patterns. However, this outperformance is not absolute.
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