An Introduction to Wavelets and Other Filtering Methods in Finance and Economics

An Introduction to Wavelets and Other Filtering Methods in Finance and Economics PDF Author: Ramazan Gençay
Publisher: Elsevier
ISBN: 0080509223
Category : Business & Economics
Languages : en
Pages : 383

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Book Description
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multi-resolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method. - The first book to present a unified view of filtering techniques - Concentrates on exactly what wavelets analysis and filtering methods in general can reveal about a time series - Provides easy access to a wide spectrum of parametric and non-parametric filtering methods

An Introduction to Wavelets and Other Filtering Methods in Finance and Economics

An Introduction to Wavelets and Other Filtering Methods in Finance and Economics PDF Author: Ramazan Gençay
Publisher: Elsevier
ISBN: 0080509223
Category : Business & Economics
Languages : en
Pages : 383

Get Book Here

Book Description
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multi-resolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method. - The first book to present a unified view of filtering techniques - Concentrates on exactly what wavelets analysis and filtering methods in general can reveal about a time series - Provides easy access to a wide spectrum of parametric and non-parametric filtering methods

Wavelet Multiresolution Analysis of Financial Time Series

Wavelet Multiresolution Analysis of Financial Time Series PDF Author: Mikko Ranta
Publisher:
ISBN: 9789524763035
Category : Finance
Languages : en
Pages : 121

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Book Description


Wavelet Applications in Economics and Finance

Wavelet Applications in Economics and Finance PDF Author: Marco Gallegati
Publisher: Springer
ISBN: 3319070614
Category : Business & Economics
Languages : en
Pages : 271

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Book Description
This book deals with the application of wavelet and spectral methods for the analysis of nonlinear and dynamic processes in economics and finance. It reflects some of the latest developments in the area of wavelet methods applied to economics and finance. The topics include business cycle analysis, asset prices, financial econometrics, and forecasting. An introductory paper by James Ramsey, providing a personal retrospective of a decade's research on wavelet analysis, offers an excellent overview over the field.

An Introduction to Wavelet Theory in Finance

An Introduction to Wavelet Theory in Finance PDF Author: Francis In
Publisher: World Scientific
ISBN: 9814397830
Category : Business & Economics
Languages : en
Pages : 213

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Book Description
This book offers an introduction to wavelet theory and provides the essence of wavelet analysis including Fourier analysis and spectral analysis; the maximum overlap discrete wavelet transform; wavelet variance, covariance, and correlation in a unified and friendly manner. It aims to bridge the gap between theory and practice by presenting substantial applications of wavelets in economics and finance. This book is the first to provide a comprehensive application of wavelet analysis to financial markets, covering new frontier issues in empirical finance and economics. The first chapter of this unique text starts with a description of the key features and applications of wavelets. After an overview of wavelet analysis, successive chapters rigorously examine the various economic and financial topics and issues that stimulate academic and professional research, including equity, interest swaps, hedges and futures, foreign exchanges, financial asset pricing, and mutual fund markets. This detail-oriented text is descriptive and designed purely for academic researchers and financial practitioners. It assumes no prior knowledge of econometrics and covers important topics such as portfolio asset allocation, asset pricing, hedging strategies, new risk measures, and mutual fund performance. Its accessible presentation is also suitable for post-graduates in a variety of disciplines applied economics, financial engineering, international finance, financial econometrics, and fund management. To facilitate the subject of wavelets, sophisticated proofs and mathematics are avoided as much as possible when applying the wavelet multiscaling method. To enhance the reader's understanding in practical applications of the wavelet multiscaling method, this book provides sample programming instruction backed by Matlab wavelet code.

Wavelet Neural Networks

Wavelet Neural Networks PDF Author: Antonios K. Alexandridis
Publisher: John Wiley & Sons
ISBN: 1118596293
Category : Mathematics
Languages : en
Pages : 262

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Book Description
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.

Modeling Financial Time Series with S-PLUS

Modeling Financial Time Series with S-PLUS PDF Author: Eric Zivot
Publisher: Springer Science & Business Media
ISBN: 0387217630
Category : Business & Economics
Languages : en
Pages : 632

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Book Description
The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.

Technical Analysis And Financial Asset Forecasting: From Simple Tools To Advanced Techniques

Technical Analysis And Financial Asset Forecasting: From Simple Tools To Advanced Techniques PDF Author: Raymond Hon-fu Chan
Publisher: World Scientific Publishing Company
ISBN: 9814436267
Category : Business & Economics
Languages : en
Pages : 203

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Book Description
Technical analysis is defined as the tracking and prediction of asset price movements using charts and graphs in combination with various mathematical and statistical methods. More precisely, it is the quantitative criteria used in predicting the relative strength of buying and selling forces within a market to determine what to buy, what to sell, and when to execute trades. This book introduces simple technical analysis tools like moving averages and Bollinger bands, and also advanced techniques such as wavelets and empirical mode decomposition. It first discusses some traditional tools in technical analysis, such as trend, trend Line, trend channel, Gann's Theory, moving averages, and Bollinger bands. It then introduces a recent indicator developed for stock market and two recent techniques used in the technical analysis field: wavelets and the empirical mode decomposition in financial time series. The book also discusses the theory to test the performance of the indicators and introduces the MATLAB Financial Toolbox, some of the functions/codes of which are used in our numerical experiments.

Modeling Financial Time Series with S-PLUS

Modeling Financial Time Series with S-PLUS PDF Author: Eric Zivot
Publisher: Springer Science & Business Media
ISBN: 9780387955490
Category : Business & Economics
Languages : en
Pages : 648

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Book Description
The field of financial econometrics has exploded since the early 1990s. This book represents an integration of theory, methods and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. It shows the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts.

Wavelet Analysis

Wavelet Analysis PDF Author: Sabrine Arfaoui
Publisher: CRC Press
ISBN: 1000369544
Category : Mathematics
Languages : en
Pages : 255

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Book Description
Wavelet Analysis: Basic Concepts and Applications provides a basic and self-contained introduction to the ideas underpinning wavelet theory and its diverse applications. This book is suitable for master’s or PhD students, senior researchers, or scientists working in industrial settings, where wavelets are used to model real-world phenomena and data needs (such as finance, medicine, engineering, transport, images, signals, etc.). Features: Offers a self-contained discussion of wavelet theory Suitable for a wide audience of post-graduate students, researchers, practitioners, and theorists Provides researchers with detailed proofs Provides guides for readers to help them understand and practice wavelet analysis in different areas

Time Series Analysis, Modeling and Applications

Time Series Analysis, Modeling and Applications PDF Author: Witold Pedrycz
Publisher: Springer Science & Business Media
ISBN: 3642334393
Category : Technology & Engineering
Languages : en
Pages : 398

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Book Description
Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological and algorithmic approaches and case studies. This volume is aimed at a broad audience of researchers and practitioners engaged in various branches of operations research, management, social sciences, engineering, and economics. Owing to the nature of the material being covered and a way it has been arranged, it establishes a comprehensive and timely picture of the ongoing pursuits in the area and fosters further developments.