Financial Decision Making Using Computational Intelligence

2012
ISBN: 978-1-4614-3772-7
Verlag: Springer US

Buch, Englisch, Band 70, 326 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 682 g

Reihe: Springer Optimization and Its Applications

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.

Zielgruppe

Research

Autoren/Hrsg.

Doumpos, Michael

Pardalos, Panos M.

Zopounidis, Constantin

Fachgebiete

• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Finanzierung, Investition, Leasing
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik

Inhaltsverzeichnis

Preface.- List of Contributors.- 1. Statistically Principled Application of Computational Intelligence Techniques for Finance (J.V. Healy).- 2. Can Artificial Traders Learn and Err Like Human Traders? A New Direction for Computational Intelligence in Behavioral Finance (S.-H. Chen, K.-C. Shih, C.-C. Tai).- 3. Application of Intelligent Systems for News Analytics (C. Bozic, S. Chalup, D. Seese).- 4. Modelling and Trading the Greek Stock Market with Hybrid ARMA-Neural Network Models (C. L. Dunis, J. Laws, A. Karathanasopoulos).- 5. Pattern Detection and Analysis in Financial Time Series Using Suffix Arrays (K. F. Xylogiannopoulos, P. Karampelas, R. Alhajj).- 6. Genetic Programming for the Induction of Seasonal Forecasts: A Study on Weather Derivatives (A. Agapitos, M. O’Neill, A. Brabazon).- 7. Evolution Strategies for IPO Underpricing Prediction (D. Quintana, C. Luque, J. M. Valls, P. Isasi).- 8. Bayesian Networks for Portfolio Analysis and Optimization (S. Villa, F. Stella).- 9. Markov Chains in Modelling of the Russian Financial Market (G. A. Bautin and V. A. Kalyagin).- 10. Fuzzy Portfolio Selection Models: A Numerical Study (En. Vercher and J. D. Bermúdez).- 11. Financial Evaluation of Life Insurance Policies in High Performance Computing Environments (S. Corsaro, P. L. De Angelis, Z. Marino, P. Zanetti).- Index.