"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.