Ebook: Financial Decision Making Using Computational Intelligence
- Tags: Operations Research Management Science, Finance/Investment/Banking
- Series: Springer Optimization and Its Applications 70
- Year: 2012
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.
Financial Decision Making Using Computational Intelligence covers all the recent developments in complex financial decision making through computational intelligence approaches. Computational intelligence has evolved rapidly in recent years and it is now one of the most active fields in operations research and computer science. The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides a wide range of useful techniques, including new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems.
This book presents the recent advances made in financial decision making using computational intelligence, covering both new methodological developments as well as new emerging application areas. This work covers a wide range of topics related to financial decision making, financial modeling, risk management, and financial engineering, including algorithmic trading, financial time-series analysis, asset pricing, portfolio management, auction markets, and insurance services. Practitioners in the financial industry as well as operations researchers, management scientists, and data analysts will find this publication highly useful.
Financial Decision Making Using Computational Intelligence covers all the recent developments in complex financial decision making through computational intelligence approaches. Computational intelligence has evolved rapidly in recent years and it is now one of the most active fields in operations research and computer science. The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides a wide range of useful techniques, including new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems.
This book presents the recent advances made in financial decision making using computational intelligence, covering both new methodological developments as well as new emerging application areas. This work covers a wide range of topics related to financial decision making, financial modeling, risk management, and financial engineering, including algorithmic trading, financial time-series analysis, asset pricing, portfolio management, auction markets, and insurance services. Practitioners in the financial industry as well as operations researchers, management scientists, and data analysts will find this publication highly useful.
Content:
Front Matter....Pages i-xvii
Statistically Principled Application of Computational Intelligence Techniques for Finance....Pages 1-33
Can Artificial Traders Learn and Err Like Human Traders? A New Direction for Computational Intelligence in Behavioral Finance....Pages 35-69
Application of Intelligent Systems for News Analytics....Pages 71-101
Modelling and Trading the Greek Stock Market with Hybrid ARMA-Neural Network Models....Pages 103-127
Pattern Detection and Analysis in Financial Time Series Using Suffix Arrays....Pages 129-157
Genetic Programming for the Induction of Seasonal Forecasts: A Study on Weather Derivatives....Pages 159-188
Evolution Strategies for IPO Underpricing Prediction....Pages 189-208
Bayesian Networks for Portfolio Analysis and Optimization....Pages 209-232
Markov Chains in Modelling of the Russian Financial Market....Pages 233-251
Fuzzy Portfolio Selection Models: A Numerical Study....Pages 253-280
Financial Evaluation of Life Insurance Policies in High Performance Computing Environments....Pages 281-319
Back Matter....Pages 321-324
Financial Decision Making Using Computational Intelligence covers all the recent developments in complex financial decision making through computational intelligence approaches. Computational intelligence has evolved rapidly in recent years and it is now one of the most active fields in operations research and computer science. The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides a wide range of useful techniques, including new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems.
This book presents the recent advances made in financial decision making using computational intelligence, covering both new methodological developments as well as new emerging application areas. This work covers a wide range of topics related to financial decision making, financial modeling, risk management, and financial engineering, including algorithmic trading, financial time-series analysis, asset pricing, portfolio management, auction markets, and insurance services. Practitioners in the financial industry as well as operations researchers, management scientists, and data analysts will find this publication highly useful.
Content:
Front Matter....Pages i-xvii
Statistically Principled Application of Computational Intelligence Techniques for Finance....Pages 1-33
Can Artificial Traders Learn and Err Like Human Traders? A New Direction for Computational Intelligence in Behavioral Finance....Pages 35-69
Application of Intelligent Systems for News Analytics....Pages 71-101
Modelling and Trading the Greek Stock Market with Hybrid ARMA-Neural Network Models....Pages 103-127
Pattern Detection and Analysis in Financial Time Series Using Suffix Arrays....Pages 129-157
Genetic Programming for the Induction of Seasonal Forecasts: A Study on Weather Derivatives....Pages 159-188
Evolution Strategies for IPO Underpricing Prediction....Pages 189-208
Bayesian Networks for Portfolio Analysis and Optimization....Pages 209-232
Markov Chains in Modelling of the Russian Financial Market....Pages 233-251
Fuzzy Portfolio Selection Models: A Numerical Study....Pages 253-280
Financial Evaluation of Life Insurance Policies in High Performance Computing Environments....Pages 281-319
Back Matter....Pages 321-324
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