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

Authors: Ramazan Gençay, Faruk Selçuk, Brandon J. Whitcher Publisher: Elsevier Science Publication date: 2001 Publication language: Angielski Number of pages: 359 Publication formats: EAN: 9780080509228 ISBN: 9780080509228 Category: Econometrics Finance Budgeting & financial management Examinations & assessment Publisher's index: B978-0-12-279670-8.X5000-9 Bibliographic note: Brandon Whitcher is currently a visiting scientist in the Geophysical Statistics Project at the National Center for Atmospheric Research. He was a research scientist at EURANDOM, a European research institute for the study of stochastic phenomena, after receiving his Ph.D. in statistics from the University of Washington. His research interests include wavelet methodology, time series analysis, computational statistics, and applications in the physical sciences, finance, and economics. His publications have appeared in Exploration Geophysics, Journal of Computational and Graphical Statistics, Journal of Geophysical Research, Journal of Statistical Computation and Simulation, and Physica A.

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

Author's affiliation

Ramazan Gençay: Simon Fraser University, Burnaby, British Col
Faruk Selçuk: Bilkent University, Ankara, Turkey
Brandon J. Whitcher: National Center for Atmospheric Research, Bou