Neural Networks In Financial Engineering


Neural Networks In Financial Engineering
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Neural Networks In Financial Engineering


Neural Networks In Financial Engineering
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Author : Apostolos-Paul Refenes
language : en
Publisher: World Scientific Publishing Company Incorporated
Release Date : 1996

Neural Networks In Financial Engineering written by Apostolos-Paul Refenes and has been published by World Scientific Publishing Company Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Business & Economics categories.


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



Wavelet Neural Networks


Wavelet Neural Networks
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Author : Antonios K. Alexandridis
language : en
Publisher: John Wiley & Sons
Release Date : 2014-04-24

Wavelet Neural Networks written by Antonios K. Alexandridis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-24 with Mathematics categories.


A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: • Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence • Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction • An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks • Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.



Neural Networks And The Financial Markets


Neural Networks And The Financial Markets
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Author : Jimmy Shadbolt
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Neural Networks And The Financial Markets written by Jimmy Shadbolt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


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.



Decision Technologies For Financial Engineering


Decision Technologies For Financial Engineering
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Author : Andreas S. Weigend
language : en
Publisher: World Scientific
Release Date : 1998-01-02

Decision Technologies For Financial Engineering written by Andreas S. Weigend and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-01-02 with Business & Economics categories.


This volume selects the best contributions from the Fourth International Conference on Neural Networks in the Capital Markets (NNCM). The conference brought together academics from several disciplines with strategists and decision makers from the financial industries. The various chapters present and compare new techniques from many areas including data mining, information systems, machine learning, and statistical artificial intelligence. The volume focuses on evaluating their usefulness for problems in computational finance and financial engineering. Applications — risk management; asset allocation; dynamic trading and hedging; forecasting; trading cost control. Markets — equity; foreign exchange; bond; commodity; derivatives; Approaches — data mining; statistical AI; machine learning; Monte Carlo simulation; bootstrapping; genetic algorithms; nonparametric methods; fuzzy logic. The chapters emphasizes in-depth and comparative evaluation with established approaches. Contents:Decision Technologies:Optimization of Trading Systems and Portfolios (J E Moody & L Z Wu)Nonlinear versus Linear Techniques for Selecting Individual Stocks (S Mahfoud et al.)Soft Prediction of Stock Behavior (Y Baram)Risk Management:Validating a Connectionist Model of Financial Diagnosis (P E Pedersen)Neural Networks for Risk Analysis in Stock Price Forecasts (M Klenin)Optimizing Neural Network Classifiers for Bond Rating (A N Skurikhin & A J Surkan)Statistical Learning for Financial Problems:Forecasting Volatility Mispricing (P J Bolland & A N Burgess)Intraday Modeling of the Term Structure of Interest Rates (J T Connor et al.)Modeling of Nonstationary Financial Time Series by Nonparametric Data Selection (G Deco et al.)Foreign Exchange Trading and Analysis:Principal Components Analysis for Modeling Multi-Currency Porfolios (J Utans et al.)Quantization Effects and Cluster Analysis on Foreign Exchange Rates (W M Leung et al.)A Computer Simulation of Currency Market Participantsand other papers Readership: Practitioners and academics who are interested in developments and applications of data mining to finance. keywords:



Neural Networks In Finance And Investing


Neural Networks In Finance And Investing
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Author : Robert R. Trippi
language : en
Publisher: Irwin Professional Publishing
Release Date : 1996

Neural Networks In Finance And Investing written by Robert R. Trippi and has been published by Irwin Professional Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Business & Economics categories.


This completely updated version of the classic first edition offers a wealth of new material reflecting the latest developments in teh field. For investment professionals seeking to maximize this exciting new technology, this handbook is the definitive information source.



Wavelet Neural Networks


Wavelet Neural Networks
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Author : Achilleas Zapranis
language : en
Publisher:
Release Date : 2014

Wavelet Neural Networks written by Achilleas Zapranis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Engineering categories.


A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.



Financial Prediction Using Neural Networks


Financial Prediction Using Neural Networks
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Author : Joseph S. Zirilli
language : en
Publisher:
Release Date : 1997

Financial Prediction Using Neural Networks written by Joseph S. Zirilli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Business & Economics categories.


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.



Practical Applications Of Evolutionary Computation To Financial Engineering


Practical Applications Of Evolutionary Computation To Financial Engineering
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Author : Hitoshi Iba
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-15

Practical Applications Of Evolutionary Computation To Financial Engineering written by Hitoshi Iba and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-15 with Technology & Engineering categories.


“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.



Neural Networks In Finance


Neural Networks In Finance
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Author : Paul D. McNelis
language : en
Publisher: Academic Press
Release Date : 2005-01-05

Neural Networks In Finance written by Paul D. McNelis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-05 with Business & Economics categories.


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



Artificial Neural Networks In Finance And Manufacturing


Artificial Neural Networks In Finance And Manufacturing
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Author : Kamruzzaman, Joarder
language : en
Publisher: IGI Global
Release Date : 2006-03-31

Artificial Neural Networks In Finance And Manufacturing written by Kamruzzaman, Joarder and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-31 with Computers categories.


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