Overview

Recent years have seen the widespread application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechanisms drawn from Natural Computing algorithms for the purposes of agent-based modelling in finance and economics. In this book we have collected a series of chapters which illustrate these two faces of Natural Computing. The first part of the book illustrates how algorithms inspired by the natural world can be used as problem solvers to uncover and optimise financial models. The second part of the book examines a number agent-based simulations of financial systems. This book follows on from Natural Computing in Computational Finance (Volume 100 in Springer’s Studies in Computational Intelligence series) which in turn arose from the success of EvoFIN 2007, the very first European Workshop on Evolutionary Computation in Finance & Economics held in Valencia, Spain in April 2007.

Full Product Details

Author:   Anthony Brabazon ,  Michael O'Neill
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of hardcover 1st ed. 2009
Volume:   185
Dimensions:   Width: 15.50cm , Height: 1.30cm , Length: 23.50cm
Weight:   0.454kg
ISBN:  

9783642101120

ISBN 10:   3642101127
Pages:   250
Publication Date:   28 October 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Natural Computing in Computational Finance (Volume 2): Introduction.- Natural Computing in Computational Finance (Volume 2): Introduction.- I Financial Modelling.- Statistical Arbitrage with Genetic Programming.- Finding Relevant Variables in a Financial Distress Prediction Problem Using Genetic Programming and Self-organizing Maps.- Ant Colony Optimization for Option Pricing.- A Neuro-Evolutionary Approach for Interest Rate Modelling.- Who’s Smart and Who’s Lucky? Inferring Trading Strategy, Learning and Adaptation in Financial Markets through Data Mining.- II Agent-Based Modelling.- Financial Bubbles: A Learning Effect Modelling Approach.- Evolutionary Computation and Artificial Financial Markets.- Classical and Agent-Based Evolutionary Algorithms for Investment Strategies Generation.- Income Distribution and Lottery Expenditures in Taiwan: An Analysis Based on Agent-Based Simulation.- The Emergence of a Market: What Efforts Can Entrepreneurs Make?.

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