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Neural Networks in Finance

Author: Paul D. McNelis

Publisher: Academic Press

Published: 2005-01-05

Total Pages: 262

ISBN-13: 0124859674

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This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website

Book Synopsis Neural Networks in Finance by : Paul D. McNelis

Download or read book Neural Networks in Finance written by Paul D. McNelis and published by Academic Press. This book was released on 2005-01-05 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website

Neural Networks and the Financial Markets

Author: Jimmy Shadbolt

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 266

ISBN-13: 1447101510

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This volume looks at financial prediction from a broad range of perspectives. It covers: - the economic arguments - the practicalities of the markets - how predictions are used - how predictions are made - how predictions are turned into something usable (asset locations) It combines a discussion of standard theory with state-of-the-art material on a wide range of information processing techniques as applied to cutting-edge financial problems. All the techniques are demonstrated with real examples using actual market data, and show that it is possible to extract information from very noisy, sparse data sets. Aimed primarily at researchers in financial prediction, time series analysis and information processing, this book will also be of interest to quantitative fund managers and other professionals involved in financial prediction.

Book Synopsis Neural Networks and the Financial Markets by : Jimmy Shadbolt

Download or read book Neural Networks and the Financial Markets written by Jimmy Shadbolt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume looks at financial prediction from a broad range of perspectives. It covers: - the economic arguments - the practicalities of the markets - how predictions are used - how predictions are made - how predictions are turned into something usable (asset locations) It combines a discussion of standard theory with state-of-the-art material on a wide range of information processing techniques as applied to cutting-edge financial problems. All the techniques are demonstrated with real examples using actual market data, and show that it is possible to extract information from very noisy, sparse data sets. Aimed primarily at researchers in financial prediction, time series analysis and information processing, this book will also be of interest to quantitative fund managers and other professionals involved in financial prediction.

Neural Network Solutions for Trading in Financial Markets

Author: Dirk Emma Baestaens

Publisher: Pitman Publishing

Published: 1994

Total Pages: 274

ISBN-13:

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Offers an alternative technique in forecasting to the traditional techniques used in trading and dealing. The book explains the shortcomings of traditional techniques and shows how neural networks overcome many of the disadvantages of these traditional systems.

Book Synopsis Neural Network Solutions for Trading in Financial Markets by : Dirk Emma Baestaens

Download or read book Neural Network Solutions for Trading in Financial Markets written by Dirk Emma Baestaens and published by Pitman Publishing. This book was released on 1994 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers an alternative technique in forecasting to the traditional techniques used in trading and dealing. The book explains the shortcomings of traditional techniques and shows how neural networks overcome many of the disadvantages of these traditional systems.

Neural Network Time Series

Author: E. Michael Azoff

Publisher:

Published: 1994-09-27

Total Pages: 224

ISBN-13:

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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.

Book Synopsis Neural Network Time Series by : E. Michael Azoff

Download or read book Neural Network Time Series written by E. Michael Azoff and published by . This book was released on 1994-09-27 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Neural Networks in Finance

Author: Paul D. McNelis

Publisher: Elsevier

Published: 2005-01-20

Total Pages: 261

ISBN-13: 0080479650

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Book Synopsis Neural Networks in Finance by : Paul D. McNelis

Download or read book Neural Networks in Finance written by Paul D. McNelis and published by Elsevier. This book was released on 2005-01-20 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website

Financial Prediction Using Neural Networks

Author: Joseph S. Zirilli

Publisher:

Published: 1997

Total Pages: 168

ISBN-13:

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Focusing on approaches to performing trend analysis through the use of neural nets, this book comparess the results of experiments on various types of markets, and includes a review of current work in the area. It appeals to students in both neural computing and finance as well as to financial analysts and academic and professional researchers in the field of neural network applications.

Book Synopsis Financial Prediction Using Neural Networks by : Joseph S. Zirilli

Download or read book Financial Prediction Using Neural Networks written by Joseph S. Zirilli and published by . This book was released on 1997 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on approaches to performing trend analysis through the use of neural nets, this book comparess the results of experiments on various types of markets, and includes a review of current work in the area. It appeals to students in both neural computing and finance as well as to financial analysts and academic and professional researchers in the field of neural network applications.

Artificial Neural Networks in Finance and Manufacturing

Author: Kamruzzaman, Joarder

Publisher: IGI Global

Published: 2006-03-31

Total Pages: 299

ISBN-13: 1591406722

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"This book presents a variety of practical applications of neural networks in two important domains of economic activity: finance and manufacturing"--Provided by publisher.

Book Synopsis Artificial Neural Networks in Finance and Manufacturing by : Kamruzzaman, Joarder

Download or read book Artificial Neural Networks in Finance and Manufacturing written by Kamruzzaman, Joarder and published by IGI Global. This book was released on 2006-03-31 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents a variety of practical applications of neural networks in two important domains of economic activity: finance and manufacturing"--Provided by publisher.

Artificial Intelligence in Financial Markets

Author: Christian L. Dunis

Publisher: Springer

Published: 2016-11-21

Total Pages: 349

ISBN-13: 1137488808

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As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Book Synopsis Artificial Intelligence in Financial Markets by : Christian L. Dunis

Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Neural Networks for Economic and Financial Modelling

Author: Andrea Beltratti

Publisher:

Published: 1996

Total Pages: 312

ISBN-13:

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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.

Book Synopsis Neural Networks for Economic and Financial Modelling by : Andrea Beltratti

Download or read book Neural Networks for Economic and Financial Modelling written by Andrea Beltratti and published by . This book was released on 1996 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Neural Networks in Financial Engineering

Author: Apostolos-Paul Refenes

Publisher: World Scientific Publishing Company Incorporated

Published: 1996

Total Pages: 634

ISBN-13: 9789810228194

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Neural networks can be used for improving investment performance in the financial markets. The papers in this volume aim to give investment managers, institutional investors and analysts a comprehensive look at the most profitable applications of this tech

Book Synopsis Neural Networks in Financial Engineering by : Apostolos-Paul Refenes

Download or read book Neural Networks in Financial Engineering written by Apostolos-Paul Refenes and published by World Scientific Publishing Company Incorporated. This book was released on 1996 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks can be used for improving investment performance in the financial markets. The papers in this volume aim to give investment managers, institutional investors and analysts a comprehensive look at the most profitable applications of this tech