Natural Computing in Computational Finance: Volume 4

Overview

This book follows on from Natural Computing in Computational Finance Volumes I, II and III.As in the previous volumes of this series, thebook consists of a series of 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-based methodologies in computational finance and economics.

The applications explored include ...

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Overview

This book follows on from Natural Computing in Computational Finance Volumes I, II and III.As in the previous volumes of this series, thebook consists of a series of 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-based methodologies in computational finance and economics.

The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are

written so that they are accessible to a wide audience. Hence, they should be of interestto academics, students and practitioners in the fields of computational finance and economics.

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-based methodologies in computational finance and economics.

The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are

written so that they are accessible to a wide audience. Hence, they should be of interestto academics, students and practitioners in the fields of computational finance and economics.

The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are

written so that they are accessible to a wide audience. Hence, they should be of interestto academics, students and practitioners in the fields of computational finance and economics.

written so that they are accessible to a wide audience. Hence, they should be of interestto academics, students and practitioners in the fields of computational finance and economics.

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Product Details

  • ISBN-13: 9783642233357
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 9/28/2011
  • Series: Studies in Computational Intelligence Series , #380
  • Edition description: 2012
  • Edition number: 1
  • Pages: 202
  • Product dimensions: 6.10 (w) x 9.20 (h) x 0.60 (d)

Table of Contents

1 Natural Computing in Computational Finance (Volume 4): Introduction.- 2 Calibrating Option Pricing Models with Heuristics.- 3 A Comparison Between Nature-Inspired and Machine Learning Approaches to Detecting Trend Reversals in Financial Time Series.- 4 A soft computing approach to enhanced indexation.- 5 Parallel Evolutionary Algorithms for Sk Market Trading Rule Selection on Many-Core Graphics Processors.- 6 Regime-Switching Recurrent Reinforcement Learning in Automated Trading.- 7 An Evolutionary Algorithmic Investigation of US Corporate Payout Policy Determination.- 8 Tackling Overfitting in Evolutionary-driven Financial Model Induction.- 9 An Order-Driven Agent-Based Artificial Sk Market to Analyze Liquidity Costs of Market Orders in the Taiwan Sk Market.- 10 Market Microstructure: A Self-Organizing Map Approach to Investigate Behavior Dynamics under an Evolutionary Environment.

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