NDLI: A comparative survey of three AI techniques (NN, PSO, and GA) in financial domain

Content Provider	IEEE Xplore Digital Library
Author	Beiranvand, V. Abu Bakar, A. Othman, Z.
Copyright Year	2012
Description	Author affiliation: Center for Artificial Intell. Technol., Univ. Kebangsaan Malaysia, Bangi, Malaysia (Beiranvand, V.; Abu Bakar, A.; Othman, Z.)
Abstract	In the real world, the behaviors of financial applications are unstable and they change from time to time. Accordingly, dealing with such issues as nonlinear and time variant problems has been a serious problem in recent years. These types of problems along with inefficiency of the traditional models led to an increasing interest in artificial intelligence approaches. In this study, we briefly review three popular artificial intelligence methods, i.e., Artificial Neural Networks, Genetic Algorithms, and Particle Swarm Optimization, and compare their applications in financial domain. By considering the broad domain of financial applications, we classify financial market into three domains, including financial forecasting, credit evaluation, and portfolio management. For each technique, we have attempted to take the most recent and popular studies into account. The results are promising and represent that in handling financial problems, the performance and accuracy of the above mentioned artificial intelligence techniques are considerably higher, compared to the traditional statistical techniques, particularly in nonlinear models. Nevertheless, this superiority is not true in all cases.
Sponsorship	IEEE Korea Council
Starting Page	332
Ending Page	337
File Size	768106
Page Count	6
File Format	PDF
ISBN	9781467308946
e-ISBN	9788994364223
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-03
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	AICIT
Subject Keyword	Artificial neural networks Financial prediction and planning Genetic Algorithms Portfolio management Particle Swarm Optimization Credit evaluation
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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