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A Knowledge Representation Framework for Facilitating Online Investing

A Knowledge Representation Framework for Facilitating Online Investing
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Author(s): Myron Sheu (California State University, Long Beach, USA), Melody Kiang (California State University, Long Beach, USA), Peter A. Ammermann (California State University, Long Beach, USA) and Jasmine Yur-Austin (California State University, Long Beach, USA)
Copyright: 2001
Pages: 4
Source title: Managing Information Technology in a Global Economy
Source Editor(s): Mehdi Khosrow-Pour (Information Resources Management Association, USA)
DOI: 10.4018/978-1-930708-07-5.ch111

Abstract

With the rise of the Internet and online investing, investors now have ready access to a wide variety of investment-related information. Thus, the challenge for investors is no longer how to obtain basic data necessary for making informed investment decisions, but how to quickly process and assimilate all the data that is available. In light of this change in environment, this paper examines the shortcomings of the traditional ways in which brokerage firms have provided information to their clients and then examines and develops a knowledge representation (KR) framework for better facilitating the information needs of the clients. Specifically, this paper develops a basis for situating the KR of online investing within an object-oriented framework, based on which the paper examines how implicit reasoning can be applied to deliver knowledge that is fundamental for making intelligent investment decisions but is often overlooked by online investors. However, not all investment-related information is tied to the financial markets; some information, such as risk-tolerance level and investment time horizon, is investor-specific. Thus, the paper also discusses how to incorporate such investor-specific information into the KR. Finally, the paper discusses the feasibility of implementing such a KR framework and some of the promises and pitfalls that could be expected from such a framework.

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