Springer Financial Decision Making Using Computational Intelligence: 70 (Springer Optimization and Its Applications, 70)

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.   From the Back Cover 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.