Natural Computing in Computational Finance [recurso electrónico] / edited by Anthony Brabazon, Michael O’Neill, Dietmar G. Maringer.

Por: Brabazon, Anthony [editor.]Colaborador(es): O’Neill, Michael [editor.] | Maringer, Dietmar G [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries 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 portador: online resourceISBN: 9783642139505Tema(s): Engineering | Artificial intelligence | Economics | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | Economics generalFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
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 Trader’s 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.
En: 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.
Star ratings
    Valoración media: 0.0 (0 votos)
Existencias
Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos Q342 (Browse shelf(Abre debajo)) 1 No para préstamo 374629-2001

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 Trader’s 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.

19

Con tecnología Koha