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Applying Artificial Intelligence to Financial Investing

Applying Artificial Intelligence to Financial Investing
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Author(s): Hayden Wimmer (Georgia Southern University, USA) and Roy Rada (University of Maryland – Baltimore County, USA)
Copyright: 2019
Pages: 16
Source title: Advanced Methodologies and Technologies in Business Operations and Management
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7362-3.ch001

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Abstract

Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring, and bankruptcy prediction, to name a few. While there are many subfields to artificial intelligence, this work seeks to identify the most commonly applied AI techniques to financial investing as appears in academic literature. AI techniques, such as knowledge-based, machine learning, and natural language processing, are integrated into systems that simultaneously address data identification, asset valuation, and risk management. Future trends will continue to integrate hybrid artificial intelligence techniques into financial investing, portfolio optimization, and risk management. The remainder of this chapter summarizes key contributions of applying AI to financial investing as appears in the academic literature.

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