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by Andrea Beltratti,Margarita P. Terna
Download Neural Networks for Economic and Financial Modelling fb2
Computer Science
  • Author:
    Andrea Beltratti,Margarita P. Terna
  • ISBN:
    1850321698
  • ISBN13:
    978-1850321699
  • Genre:
  • Publisher:
    Thomson Learning; 1st edition (December 21, 1995)
  • Pages:
    400 pages
  • Subcategory:
    Computer Science
  • Language:
  • FB2 format
    1733 kb
  • ePUB format
    1549 kb
  • DJVU format
    1286 kb
  • Rating:
    4.1
  • Votes:
    174
  • Formats:
    rtf azw docx txt


As Beltratti, Margarita and Terna (hereafter BMT) put it, "The specific functional forms used in nonlinear models imply of course that in general the function that generates the data is different from the one implied by ANNs. p. 8), so that the appropriate econometric theory for ANNs is that for misspecified non-linear models.

In economic and financial modelling based on ANN, the seminal work in this area was the publication of Beltratti, Margarita and Terna

In economic and financial modelling based on ANN, the seminal work in this area was the publication of Beltratti, Margarita and Terna. There is a wide collection of models in scientific literature and pragmatic too, usable after a suitable adjustment as contents blocks to building bodies of variable economic softbots. Creating New Knowledge Assisted by Computational Devices. Author is focuses attention to new possibilities of fostering creative abilities and gaining new socio-economic knowledge by the assistance of ICT, Internet and mainly by using products and services of computational intelligence.

This book investigates the use of neural networks in developing real-world applications to help economists and financial strategists predict the movement of the markets.

Andrea Beltratti, S. Margarita, P. Terna. The field of economics and finance is one of the few areas where the need for neural network applications is increasing. This book investigates the use of neural networks in developing real-world applications to help economists and financial strategists predict the movement of the markets.

Includes bibliographical references (p. -279) and index

Includes bibliographical references (p. -279) and index. I ask only once a year: please help the Internet Archive today.

Economic models and decision-making Artificial neural networks and genetic algorithms Neural networks and .

Economic models and decision-making Artificial neural networks and genetic algorithms Neural networks and economics One-agent models One-population models Multi-population models The cross-target method From artificial to real financial markets. oceedings{F, title {Neural Networks for Economic and Financial Modelling}, author {Andrea Beltratti and Sergio Margarita and Pietro Terna}, year {1995} }. Andrea Beltratti, Sergio Margarita, Pietro Terna.

Are you sure you want to remove Neural networks for economic and financial modelling from your list? . by Andrea Beltratti, Margarita P. There's no description for this book yet.

Are you sure you want to remove Neural networks for economic and financial modelling from your list? Neural networks for economic and financial modelling. Includes bibliographical references (p.

Andrea Beltratti, Pietro Terna. Luca Dalla Valle marked it as to-read Nov 14, 2010.

Neural networks for economic and financial modelling. Neural networks for economic and financial modelling.

This book emphasizes the theoretical applications of artificial neural networks to economics and finance. Its main aim is to show that the tools that are used as standard practice in one field may be fruitfully applied to tackle other problems. Specifically, the authors propose ways of looking at economic issues and clarify that neural networks may be applied, at both theoretical and practical levels, to relevant economic questions.A notable feature of Neural Networks for Economic and Financial Modelling is its coverage of the modelling of artificial agents and markets, a topic that has received considerably less attention in the available literature than the use of neural networks in purely financial applications.This book should appeal to economists interested in adopting an interdisciplinary approach to the study of economic problems, computer scientists who are looking for potential applications of artificial neural networks, and practitioners who are looking for new perspectives on how to use models for everyday operations.

Runehammer
I found that this bood went too much into the theoretical aspects of neural networks and did not rigorously go into a concrete example to back up their models. They skipped many steps in their analysis when going through examples; it would be nice to see where exactly their numbers come from so one can replicate a neural network for financial modeling at home.
Other than that, this book is quite solid. But without concrete, simplified examples, the less knowledgeable reader may not get much out of it.
Jia
This is one of best books to kick start your NN in econ and fin. Highly recommeded. It has tons of examples.