Affiliations: [a] Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD 21250, USA | [b] Department of Management Science and Economics, Coppin State University, Baltimore, MD 21216, USA
Abstract: Modern financial investing squarely depends on computing, and the role of intelligent decision technologies in investing is a lively research topic that is approached differently by each discipline. In this study, the hypothesis is that the IEEE Engineering Society literature about financial applications will 1) reveal a move over the years from a focus on expert systems tools to a focus on evolutionary computing tools 2) a continuous emphasis on applications about asset valuation, 3) highlight specific patterns across disciplines of the IEEE and 4) show a new trend to combine expert systems with evolutionary computation. A search on the IEEE literature retrieved 71 relevant articles which were systematically analyzed. All four hypotheses were supported. Most of those articles came from journals which emphasize a tool, such as neural networks. For those tool-based journals an application to finance typically only appeared in a special issue on finance, as generally, the IEEE journals explicitly prefer research addressing engineering rather than financial applications. Surprisingly, the IEEE Transactions on Power Systems regularly published new artificial intelligence approaches to financial problems because power systems professionals manage energy commodities.
Keywords: Finance, artificial intelligence, engineering, literature review
