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Article type: Research Article
Authors: Nair, Binoy B.; * | Mohandas, V.P.
Affiliations: Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amrita Nagar, Coimbatore, India
Correspondence: [*] Corresponding author: Binoy B. Nair, Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amrita Nagar, Coimbatore, PIN-641112, India. Tel.: +91 999 4375 559; E-mail: b_binoy@cb.amrita.edu
Abstract: Financial forecasting is an area of research which has been attracting a lot of attention recently from practitioners in the field of artificial intelligence. Apart from the economic benefits of accurate financial prediction, the inherent nonlinearities in financial data make the task of analyzing and forecasting an extremely challenging task. This paper presents a survey of more than 100 articles published over two centuries (from 1933 up to 2013) in an attempt to identify the developments and trends in the field of financial forecasting with focus on application of artificial intelligence for the purpose. The findings from the survey indicate that artificial intelligence and signal processing based techniques are more efficient when compared to traditional financial forecasting techniques and these techniques appear well suited for the task of financial forecasting. Some of the issues that need addressing are discussed in brief. A novel technique for selection of the input dataset size for ensuring best possible forecast accuracy is also presented. The results confirm the effectiveness of the proposed technique in improving the accuracy of forecasts.
Keywords: Artificial intelligence, financial forecasting, signal processing, soft computing, stock market, survey
DOI: 10.3233/IDT-140211
Journal: Intelligent Decision Technologies, vol. 9, no. 2, pp. 99-140, 2015
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