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Natural Computing in Computational Finance [electronic resource] / edited by Anthony Brabazon, Michael ONeill, Dietmar G. Maringer.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Studies in Computational Intelligence ; 293 | Studies in Computational Intelligence ; 293Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Descripción: 241p. 19 illus. in color. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783642139505
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 006.3 23
Clasificación LoC:
  • Q342
Recursos en línea:
Contenidos:
Springer eBooksResumen: This book consists of eleven chapters each of which was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-basedmethodologies in computational finance and economics. While describing cutting edge applications, the chapters are written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. The inspiration for this book was due in part to the success of EvoFIN 2009, the 3rd European Workshop on Evolutionary Computation in Finance and Economics. This book follows on from Natural Computing in Computational Finance Volumes I and II.
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Natural Computing in Computational Finance (Volume 3): Introduction -- Natural Computing in Computational Finance (Volume 3): Introduction -- I: Financial and Agent-Based Models -- Robust Regression with Optimisation Heuristics -- Evolutionary Estimation of a Coupled Markov Chain Credit Risk Model -- Evolutionary Computation and Trade Execution -- Agent-Based Co-operative Co-evolutionary Algorithms for Multi-objective Portfolio Optimization -- Inferring Traders Behavior from Prices -- II: Dynamic Strategies and Algorithmic Trading -- Index Mutual Fund Replication -- Frequent Knowledge Patterns in Evolutionary Decision Support Systems for Financial Time Series Analysis -- Modeling Turning Points in Financial Markets with Soft Computing Techniques -- Evolutionary Money Management -- Interday and Intraday Stock Trading Using Probabilistic Adaptive Mapping Developmental Genetic Programming and Linear Genetic Programming.

This book consists of eleven chapters each of which was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-basedmethodologies in computational finance and economics. While describing cutting edge applications, the chapters are written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. The inspiration for this book was due in part to the success of EvoFIN 2009, the 3rd European Workshop on Evolutionary Computation in Finance and Economics. This book follows on from Natural Computing in Computational Finance Volumes I and II.

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