Financial Decision Making Using Computational Intelligence
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.

1109327421
Financial Decision Making Using Computational Intelligence
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.

109.99 In Stock
Financial Decision Making Using Computational Intelligence

Financial Decision Making Using Computational Intelligence

Financial Decision Making Using Computational Intelligence

Financial Decision Making Using Computational Intelligence

Paperback(2012)

$109.99 
  • SHIP THIS ITEM
    In stock. Ships in 6-10 days.
  • PICK UP IN STORE

    Your local store may have stock of this item.

Related collections and offers


Overview

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.


Product Details

ISBN-13: 9781489990082
Publisher: Springer US
Publication date: 08/08/2014
Series: Springer Optimization and Its Applications , #70
Edition description: 2012
Pages: 326
Product dimensions: 6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

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 Sk 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.

From the B&N Reads Blog

Customer Reviews