An Introduction To Wavelet Theory In Finance


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An Introduction to Wavelet Theory in Finance


An Introduction to Wavelet Theory in Finance

Author: Francis In

language: en

Publisher: World Scientific

Release Date: 2013


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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.

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


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

Author: Ramazan Gençay

language: en

Publisher: San Diego : Academic Press

Release Date: 2002


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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 Theory and Its Application to Pattern Recognition


Wavelet Theory and Its Application to Pattern Recognition

Author: Yuan Yan Tang

language: en

Publisher: World Scientific

Release Date: 2000


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This is not a purely mathematical book. It presents the basic principle of wavelet theory to electrical & electronic engineers, computer scientists, & students, as well as the ideas of how wavelets can be applied to pattern recognition. It also contains many novel research results from the authors' research team. Contents: The Basic Concept of the Wavelet Theory in the View of Engineers; Application of Wavelet Transform to Pattern Recognition Including Document Analysis, Character Recognition, etc; Application of Wavelet Transform to Some Topics of Image Processing Used in Pattern Recognition.