Product 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

Product Details

• Amazon Sales Rank: #684156 in Books
• Published on: 2001-09-26
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 359 pages

Review
"There are many books on linear filters and wavelets, but there is only one book, Gençay, Selçuk, and Whitcher, that provides an introduction to the field for economists and financial analysts and the motivation to study the subject…..[it] contains many practical economic and financial examples that will stimulate academic and professional research for years to come…a most welcome addition to the wavelet literature."
James B. Ramsey, Professor of Economics, New York University, USA

"...particularly recommended for any time series econometrician wanting to keep up to date".
Clive W. Granger, Professor of Economics, University of California, San Diego, USA

"This timely volume will be of interest to anyone who wants to understand the latest technology for analyzing economic and financial time series. The authors are to be commended for their clear and comprehensive presentation of a fascinating and powerful approach to time-series analysis".
Halbert White, University of California, San Diego, USA -- Review

Review
Prepublication Reviews
"The authors present, in a simple fashion, a new class of filters that greatly expands on those previously available, allowing greater flexibility and generating models with time-varying specifications. The book considers familiar techniques and shows how these can be viewed in new ways, illustrating them with empirical studies from finance. It is particularly recommended for any time series econometrician wanting to keep up to date."
--CLIVE W.J. GRANGER, Professor of Economics, University of California, San Diego
"There are many books on linear filters and wavelets, but there is only one book, Gencay, Selcuk, and Whitcher, that provides an introduction to the field for economists and financial analysts and the motivation to study the subject. This book contains many practical economic and financial examples that will stimulate academic and professional research for years to come. This book is a most welcome addition to the wavelet literature."
--JAMES B. RAMSEY, Professor of Economics, New York University
"The authors have provided a very comprehensive account of the filtering literature, including wavelets, a tool not widely used in economics and finance. The volume includes many numerical illustrations, and should be accessible to a wide range of researchers."
--PETER M. ROBINSON, Tooke Professor of Economic Science and Statistics and Leverhulme Research Professor, London School of Economics, U.K.
"This timely volume will be of interest to anyone who wants to underst and the latest technology for analyzing economic and financial time series. The authors are to be commended for their clear and comprehensive presentation of a fascinating and powerful approach to time-series analysis."
--Halbert White, University of California, San Diego
Reviews
"This book sells itself short by being called "An Introduction..." OK, so it does start at the ground floor, but this is one skyscraper of a book. Without any reservations we give it the thumbs up."
-www.Wilmott.com
"...the book is a stimulating introduction which [will] induce the reader to further development and application of the wavelets and the neural networks in the fields of econometrics and finance."
--MATHEMATICAL REVIEWS

From the Back Cover
"The authors present, in a simple fashion, a new class of filters that greatly expands on those previously available, allowing greater flexibility and generating models with time-varying specifications. The book considers familiar techniques and shows how these can be viewed in new ways, illustrating them with empirical studies from finance. It is particularly recommended for any time series econometrician wanting to keep up to date."
--Clive W. J. Granger, Professor of Economics, University of California, San Diego
"There are many books on linear filters and wavelets, but there is only one book, Gençay, Selçuk, and Whitcher, that provides an introduction to the field for economists and financial analysts and the motivation to study the subject. This book contains many practical economic and financial examples that will stimulate academic and professional research for years to come. This book is a most welcome addition to the wavelet literature."
--James B. Ramsey, Professor of Economics, New York University
"The authors have provided a very comprehensive account of the filtering literature, including wavelets, a tool not widely used in economics and finance. The volume includes many numerical illustrations, and should be accessible to a wide range of researchers."
--Peter M. Robinson, Tooke Professor of Economic Science and Statistics and Leverhulme Research Professor, London School of Economics, U.K.
"This timely volume will be of interest to anyone who wants to understand the latest technology for analyzing economic and financial time series. The authors are to be commended for their clear and comprehensive presentation of a fascinating and powerful approach to time-series analysis."
--Halbert White, University of California, San Diego
What can wavelet analysis tell us about time series? Filled with empirical applications from economics and finance, this book presents a unified view of filtering techniques. It provides easy access to a wide spectrum of parametric and nonparametric filtering methods, moving from older, well-known methods to newer ones. Avoiding proofs as much as possible and emphasizing explanations and underlying theories, the authors ensure that both those who are familiar with wavelets and those who ought to be have a definitive book that reveals the capabilities, advantages, and disadvantages of each method.

Customer Reviews

The Guide
Various types of non-stationarities are common in time series data from financial markets. This requires a guide for selecting among numerous tools to deal with the non-stationarity. A unified treatment of filters like this book is a great help since it provides a fast and rigorous introduction.

Chapter 2 is on the general linear filtering theory with cleverly designed applications for illustrative purposes. "Optimum Linear Estimation" is the focus of Chapter 3 in which the Wiener Filter and the Kalman Filters among others are studied. Chapter 4 is on Discrete Wavelet Transforms and provides applications like filtering intraday seasonality in FX market and an examination of the relation between money growth and inflation. Long memory processes with seasonal components are analyzed using wavelets in Chapter 5. Denoising of economics and financial time series is the topic of Chapter 6. The decomposition of variance across different frequency bands as well as the cross-covariance between two time-series at different scales is covered in Chapter 7. Finally, Chapter 8 is on artificial neural networks in which both an introduction to the concept and some design issues with appropriate model selection criteria are provided.

Discussison of these relatively advanced topics is very simple and clear without sacrificing important details. Highly recommended.

Easy to understand!
The book is a wonderful reference in that it brings together various filtering methods. It is an excellent introduction to the topic, clearly written and easy to understand. The text does not assume a high-level math background. Further, unlike the various books which simply provide the theory but include very few or no applications at all, this book by Gencay, Selcuk, and Whitcher has many applications that help you get the right picture.