Notes: "Originally published in 1996 as a special issue journal, Artificial Intelligence Applications on Wall Street, presents a series of articles derived from papers at the Third International Conference on Artificial Intelligence Applications on Wall Street. The volume addresses how Artificial Intelligence can be used to address the variety of issues in that arise in the world of investments, such as synthetic instruments, forecasting and surveillance. It examines the potential problems surrounding economic assumption of rationality in a global market, and how artificial intelligence can push the bounds of rationality. "--Provided by publisher.

Artificial intelligence technology is being introduced on Wall Street to support the buying and selling of financial products and commodities. These applications focus on topics such as credit assessment, risk management, automated news understanding, and market surveillance. The intelligence tools that work on Wall Street are those that are modeled on successful cognitive models. The models currently used in Wall Street can be improved through cooperation of components and through collaborative models that take into account the need to meld human judgment and expert systems. Although human judgment can be faulty, either because of inconsistency, an inability to revise opinions, or a lack of expertise, the analytic models produced by intelligent systems can also be faulty. These models can err in providing incomplete explanations, incomplete model outputs and inputs, and incomplete theories.