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

Erscheinungsjahr 2001
ISBN: 978-0-12-279670-8
Verlag: William Andrew Publishing

Buch, Englisch, 384 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 640 g

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.

Zielgruppe

Undergraduate and postgraduate students as well as professionals in economics and finance. Courses include econometrics, applied economic analysis, economic statistics, probability and statistics.

Autoren/Hrsg.

Gençay, Ramazan

Selçuk, Faruk

Whitcher, Brandon J.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik

Inhaltsverzeichnis

Preface
Introduction
Linear Filters
Optimum Linear Estimation
Discrete Wavelet Transforms
Wavelets and Stationary Processes
Wavelet Denoising
Wavelets for Variance-Covariance Estimation
Artificial Neural Networks

Über Autor(innen)

Selçuk, Faruk
Faruk Selçuk is a faculty member in the department of economics at Bilkent University, Ankara, Turkey. His research interests are time series analysis, financial econometrics, risk management, emerging market economies, and the Turkish economy. His recent publications appeared in Studies in Nonlinear Dynamics and Econometrics, International Journal of Forecasting, and Physica A. He is a consultant for Reuters-Istanbul and Reuters-Moscow.

Whitcher, Brandon J.
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.

Gençay, Ramazan
Ramazan Gençay is a professor in the economics department at Simon Fraser University. His areas of specialization are financial econometrics, nonlinear time series, nonparametric econometrics, and chaotic dynamics. His publications appear in finance, economics, statistics and physics journals. His work has appeared in the Journal of the American Statistical Association, Journal of Econometrics, and Physics Letters A.

Ramazan Gençay, University of Windsor, Ontario, Canada.
Ramazan Gençay is a professor in the economics department at the University of Windsor, Ontario, Canada. His areas of specialization are financial econometrics, nonlinear time series, nonparametric econometrics, and chaotic dynamics. His publications appear in finance, economics, statistics and physics journals. Some of his publications are published in the Journal of the American Statistical Association, Journal of Econometrics, Journal of International Economics, Journal of Nonparametric Statistics, Journal of Empirical Finance, Journal of Economic Dynamics and Control, Journal of Applied Econometrics, European Economic Review, Journal of Forecasting, Physica A, Physica D and Physics Letters A. He is co-editor of Studies in Nonlinear Dynamics and Econometrics and IEEE Transactions in Computational Finance. He is also a co-author of An Introduction to High-Frequency Finance (Academic Press, 2001).

Faruk Selçuk, Bilkent University, Ankara, Turkey.
Faruk Selçuk is a faculty member in the department of economics at Bilkent University, Ankara, Turkey. His research interests are time series analysis, financial econometrics, risk management, emerging market economies, and the Turkish economy. His recent publications appeared in Studies in Nonlinear Dynamics and Econometrics, International Journal of Forecasting, and Physica A. He is a consultant for Reuters-Istanbul and Reuters-Moscow.

Brandon J. Whitcher, National Center for Atmospheric Research, Boulder, Colorado, U.S.A.
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.