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A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

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Abstract

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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  1. Signals, Images, and Intelligent Systems Laboratory (LISSI/EA 3956), University PARIS-EST-Creteil (UPEC), Senart-FB Institute of Technology, Avenue Pierre Point, 77127, Lieusaint, France

    Arash Bahrammirzaee

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Appendix A

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Table 21 Abbreviation keys (alphabetical order)
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Bahrammirzaee, A. A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems. Neural Comput & Applic 19, 1165–1195 (2010). https://doi.org/10.1007/s00521-010-0362-z

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