Neural Network Time Series: Forecasting of Financial Markets

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9780471943563: Neural Network Time Series: Forecasting of Financial Markets

Neural Network Time Series Forecasting of Financial Markets E. Michael Azoff The first comprehensive and practical introduction to using neural networks in financial time series forecasting. This practical working guide shows you how to understand, design and profitably use neural network techniques in financial market forecasting. It encompasses:

  • A tutorial introduction to neural networks
  • Data preprocessing
  • Key network design issues
  • Random walk probability theory
  • Fully specified benchmarks (and code for implementing the benchmarks as pre-trained networks)
  • An overview of futures trading
  • Discussion of trading systems and risk management
The book focuses on the multilayer perception, one of the most powerful and successful network architectures that is used in the majority of commercial applications, especially financial time series forecasting. The fully specified benchmarks are a unique feature of the book and will be of particular benefit if you are contemplating designing your own neural network using one of the many commercial simulators.

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From the Publisher:

Introduces the use of neural networks in forecasting and, in particular, financial time series forecasting. Provides much-needed guidance for applying predictive and decision-enhancing functions of neural nets to a wide range of global capital markets investments and futures trading.

From the Inside Flap:

Neural Network Time Series Forecasting of Financial Markets A neural network is a computer program that can recognise patterns in data, learn from this and (in the case of time series data) make forecasts of future patterns. There are now over 20 commercially available neural network programs designed for use on financial markets and there have been some notable reports of their successful application. However, like any other computer program, neural networks are only as good as the data they are given and the questions that are asked of them. Proper use of a neural network involves spending time understanding and cleaning the data: removing errors, preprocessing and postprocessing. This book takes the reader beyond the ‘black-box’ approach to neural networks and provides the knowledge that is required for their proper design and use in financial markets forecasting —with an emphasis on futures trading. Comprehensively specified benchmarks are provided (including weight values), drawn from time series examples in chaos theory and financial futures. The book covers data preprocessing, random walk theory, trading systems and risk analysis. It also provides a literature review, a tutorial on backpropagation, and a chapter on further reading and software. For the professional financial forecaster this book is without parallel as a comprehensive, practical and up-to-date guide to this important subject.

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1.

E. Michael Azoff
Editorial: John Wiley & Sons (1994)
ISBN 10: 0471943568 ISBN 13: 9780471943563
Nuevos Tapa dura Cantidad: 1
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Ergodebooks
(RICHMOND, TX, Estados Unidos de America)
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Descripción John Wiley & Sons, 1994. Hardcover. Estado de conservación: New. 1. Nº de ref. de la librería DADAX0471943568

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2.

Azoff, E. Michael
Editorial: Wiley (1994)
ISBN 10: 0471943568 ISBN 13: 9780471943563
Nuevos Tapa dura Cantidad: 1
Librería
Murray Media
(North Miami Beach, FL, Estados Unidos de America)
Valoración
[?]

Descripción Wiley, 1994. Hardcover. Estado de conservación: New. Nº de ref. de la librería P110471943568

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