Artificial Intelligence in Finance and Investing; State-Of-The-Art Technologies for Securities Selection and Portfolio Management

Artificial intelligence is one of Wall street's most promising new technologies. Used to assist investment decision-making, artificial intelligence systems can handle more information, react more quickly and make more consistent decisions than a group of human experts. In Artificial Intelligence in Finance and Investing, Robert Trippi and Jae Lee thoroughly explain how artificial intelligence systems can help to improve investment returns. Completely updated, this edition also includes sections on neural network and case-based reasoning. Practical and filled with real-life examples, the book provides all the information a financial professional needs to understand and evaluate an artificial intelligence system. For investors who want to stay on the cutting edge of technology, Artificial Intelligence in Finance and Investing will be a must read. Highlights include: overview of artificial intelligence in invesment management; components of an artificial intelligence system; portfolio selection system issues; handling investment uncertainties; practice exercises with K-FOLIO, a typical aritificial intelligence system.

In Artificial Intelligence in Finance and Investing, authors Robert Trippi and Jae Lee explain this fascinating new technology in terms that portfolio managers, institutional investors, investment analysis, and information systems professionals can understand. Using real-life examples and a practical approach, this rare and readable volume discusses the entire field of artificial intelligence of relevance to investing, so that readers can realize the benefits and evaluate the features of existing or proposed systems, and ultimately construct their own systems. Topics include using Expert Systems for Asset Allocation, Timing Decisions, Pattern Recognition, and Risk Assessment; overview of Popular Knowledge-Based Systems; construction of Synergistic Rule Bases for Securities Selection; incorporating the Markowitz Portfolio Optimization Model into Knowledge-Based Systems; Bayesian Theory and Fuzzy Logic System Components; Machine Learning in Portfolio Selection and Investment Timing, including Pattern-Based Learning and Fenetic Algorithms; and Neural Network-Based Systems. To illustrate the concepts presented in the book, the authors conclude with a valuable practice session and analysis of a typical knowledge-based system for investment management, K-FOLIO. For those who want to stay on the cutting edge of the "application" revolution, Artificial Intelligence in Finance and Investing offers a pragmatic introduction to the use of knowledge-based systems in securities selection and portfolio management.

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	Description Publisher's Notes Artificial intelligence is one of Wall street's most promising new technologies. Used to assist investment decision-making, artificial intelligence systems can handle more information, react more quickly and make more consistent decisions than a group of human experts. In Artificial Intelligence in Finance and Investing, Robert Trippi and Jae Lee thoroughly explain how artificial intelligence systems can help to improve investment returns. Completely updated, this edition also includes sections on neural network and case-based reasoning. Practical and filled with real-life examples, the book provides all the information a financial professional needs to understand and evaluate an artificial intelligence system. For investors who want to stay on the cutting edge of technology, Artificial Intelligence in Finance and Investing will be a must read. Highlights include: overview of artificial intelligence in invesment management; components of an artificial intelligence system; portfolio selection system issues; handling investment uncertainties; practice exercises with K-FOLIO, a typical aritificial intelligence system. In Artificial Intelligence in Finance and Investing, authors Robert Trippi and Jae Lee explain this fascinating new technology in terms that portfolio managers, institutional investors, investment analysis, and information systems professionals can understand. Using real-life examples and a practical approach, this rare and readable volume discusses the entire field of artificial intelligence of relevance to investing, so that readers can realize the benefits and evaluate the features of existing or proposed systems, and ultimately construct their own systems. Topics include using Expert Systems for Asset Allocation, Timing Decisions, Pattern Recognition, and Risk Assessment; overview of Popular Knowledge-Based Systems; construction of Synergistic Rule Bases for Securities Selection; incorporating the Markowitz Portfolio Optimization Model into Knowledge-Based Systems; Bayesian Theory and Fuzzy Logic System Components; Machine Learning in Portfolio Selection and Investment Timing, including Pattern-Based Learning and Fenetic Algorithms; and Neural Network-Based Systems. To illustrate the concepts presented in the book, the authors conclude with a valuable practice session and analysis of a typical knowledge-based system for investment management, K-FOLIO. For those who want to stay on the cutting edge of the "application" revolution, Artificial Intelligence in Finance and Investing offers a pragmatic introduction to the use of knowledge-based systems in securities selection and portfolio management.