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Wavelet Multiresolution Analysis Of Financial Time Series
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Book Synopsis Wavelet Methods for Time Series Analysis by : Donald B. Percival
Download or read book Wavelet Methods for Time Series Analysis written by Donald B. Percival and published by Cambridge University Press. This book was released on 2006-02-27 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to wavelet analysis 'from the ground level and up', and to wavelet-based statistical analysis of time series focuses on practical discrete time techniques, with detailed descriptions of the theory and algorithms needed to understand and implement the discrete wavelet transforms. Numerous examples illustrate the techniques on actual time series. The many embedded exercises - with complete solutions provided in the Appendix - allow readers to use the book for self-guided study. Additional exercises can be used in a classroom setting. A Web site offers access to the time series and wavelets used in the book, as well as information on accessing software in S-Plus and other languages. Students and researchers wishing to use wavelet methods to analyze time series will find this book essential.
Book Synopsis Analysis of Financial Time Series by : Ruey S. Tsay
Download or read book Analysis of Financial Time Series written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2005-09-15 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides statistical tools and techniques needed to understandtoday's financial markets The Second Edition of this critically acclaimed text provides acomprehensive and systematic introduction to financial econometricmodels and their applications in modeling and predicting financialtime series data. This latest edition continues to emphasizeempirical financial data and focuses on real-world examples.Following this approach, readers will master key aspects offinancial time series, including volatility modeling, neuralnetwork applications, market microstructure and high-frequencyfinancial data, continuous-time models and Ito's Lemma, Value atRisk, multiple returns analysis, financial factor models, andeconometric modeling via computation-intensive methods. The author begins with the basic characteristics of financialtime series data, setting the foundation for the three maintopics: Analysis and application of univariate financial timeseries Return series of multiple assets Bayesian inference in finance methods This new edition is a thoroughly revised and updated text,including the addition of S-Plus® commands and illustrations.Exercises have been thoroughly updated and expanded and include themost current data, providing readers with more opportunities to putthe models and methods into practice. Among the new material addedto the text, readers will find: Consistent covariance estimation under heteroscedasticity andserial correlation Alternative approaches to volatility modeling Financial factor models State-space models Kalman filtering Estimation of stochastic diffusion models The tools provided in this text aid readers in developing adeeper understanding of financial markets through firsthandexperience in working with financial data. This is an idealtextbook for MBA students as well as a reference for researchersand professionals in business and finance.
Book Synopsis Wavelet Multiresolution Analysis of Financial Time Series by : Mikko Ranta
Download or read book Wavelet Multiresolution Analysis of Financial Time Series written by Mikko Ranta and published by . This book was released on 2010 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modeling Financial Time Series with S-Plus by : Eric Zivot
Download or read book Modeling Financial Time Series with S-Plus written by Eric Zivot and published by Springer Verlag. This book was released on 2003 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Wavelet Transform in Financial Time Series Analysis by : Andriy Savka
Download or read book Wavelet Transform in Financial Time Series Analysis written by Andriy Savka and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelet transform, based on the theory of Fourier transform, is a powerful tool of frequency analysis, which allows to switch from time domain of time series to its frequency-representation for further study. Wavelet transformation techniques are widely used in signal processing, utilized to compress and efficiently store signal and image information with minimum loss of important details. Most economic and financial time series contain layered information about trend of the related economic phenomena, seasonal variation, and noise. The latter is usually associated with unexplained uncertainty shocks. As these three components of economic or financial time series have different frequencies, it is natural to apply frequency analysis tools to extract useful information and reduce noise (unimportant component of time series).The purpose of this thesis is to review recent study on wavelet transform techniques and their applications for denoising in economic and financial time series.The thesis begins from overview of wavelets, their connection to Fourier transform, and place in frequency analysis study. Then, Dyadic multiresolution analysis as a basic framework of discrete wavelet analysis is discussed. Next, wavelet denoising is discussed. Further, statistical methods of time series analysis are introduced. The research concludes with empirical application of denoising technique using discrete wavelet transform to analysis of the Standard & Poor's 500 stock prices index and West Texas Intermediate crude oil prices on the U.S. market.
Download or read book Time Series written by Ngai Hang Chan and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of Financial Time Series fills a gap in the market in the area of financial time series analysis by giving both conceptual and practical illustrations. Examples and discussions in the later chapters of the book make recent developments in time series more accessible. Examples from finance are maximized as much as possible throughout the book. * Full set of exercises is displayed at the end of each chapter. * First seven chapters cover standard topics in time series at a high-intensity level. * Recent and timely developments in nonstandard time series techniques are illustrated with real finance examples in detail. * Examples are systemically illustrated with S-plus with codes and data available on an associated Web site.
Book Synopsis Multivariate Time Series Analysis by : Ruey S. Tsay
Download or read book Multivariate Time Series Analysis written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2013-11-11 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.
Book Synopsis An Introduction to Wavelets and Other Filtering Methods in Finance and Economics by : Ramazan Gençay
Download or read book An Introduction to Wavelets and Other Filtering Methods in Finance and Economics written by Ramazan Gençay and published by Elsevier. This book was released on 2001-10-12 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Modern Applications of Wavelet Transform by : Srinivasan Ramakrishnan
Download or read book Modern Applications of Wavelet Transform written by Srinivasan Ramakrishnan and published by BoD – Books on Demand. This book was released on 2024-02-07 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the use of wavelet transforms in signal processing, including image, finance, and communication systems. It covers five contemporary applications, including the interaction between inertial sensors and wavelet filtering techniques, geophysical prospecting, volatility patterns in asset returns, computerized tomography (CT), and fault detection techniques. The book provides a foundation for further exploration, focusing on wavelet transformations' basic principles, their application in geophysical prospecting, and their use in identifying volatility patterns in asset returns. The book is intended for students, researchers, and professionals interested in understanding wavelet transforms and their practical implementations.
Book Synopsis Applications of Wavelet Analysis to Financial Time Series by : Andrew James Wagner
Download or read book Applications of Wavelet Analysis to Financial Time Series written by Andrew James Wagner and published by . This book was released on 1997 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction and Review Collection for Analysis of Financial Time Series by : Anuj Kumar
Download or read book Introduction and Review Collection for Analysis of Financial Time Series written by Anuj Kumar and published by LAP Lambert Academic Publishing. This book was released on 2012-07 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we have studied the properties of wavelet transform and their uses in the analysis of time series. A large number of researchers are now engaged in applying wavelets to different situations, and all are seem to report favorable results. Current physical applications of wavelets include a wide variety such as climate analysis, financial time series analysis, heart monitoring etc. The chapter-1, Introduction, is purely introductory in nature and is aimed to fulfill the basic needs of introducing the various concepts and foundation needed for the analysis of time series. Chapter-2, Review of Literature, accommodates majority of available past research works directly related with the present work. Chapter-3, Materials and Methods, covers the theory and practices currently being used and also needed for the present study for time series analysis.The chapter-4 comprises of the Results and Discussion of the problems discussed in chapter-3. This book will be useful to the researchers in financial time series analysis field or anyone else who may be considering utilizing wavelet based concepts for the same.
Book Synopsis Multiresolution Analysis of Long Time Series with Applications to Finance by : Ralph Högn
Download or read book Multiresolution Analysis of Long Time Series with Applications to Finance written by Ralph Högn and published by . This book was released on 2005 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Analysis of Financial Time-Series Using Fourier and Wavelet Methods by : Philippe Masset
Download or read book Analysis of Financial Time-Series Using Fourier and Wavelet Methods written by Philippe Masset and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents a set of tools, which allow gathering information about the frequency components of a time-series. We focus on the concepts rather than giving too much weight to mathematical technicalities. In a first step, we discuss spectral analysis and filtering methods. Spectral analysis can be used to identify and to quantify the different frequency components of a data series. Filters permit to capture specific components (e.g. trends, cycles, seasonalities) of the original time-series. Both spectral analysis and standard filtering methods have two main drawbacks: (i) they impose strong restrictions regarding the possible processes underlying the dynamics of the series (e.g. stationarity), and, (ii) they lead to a pure frequency-domain representation of the data, i.e. all information from the time-domain representation is lost in the operation. In a second step, we introduce wavelets, which are relatively new tools in economics and finance. They take their roots from filtering methods and Fourier analysis. But they overcome most of the limitations of these two methods. Indeed their principal advantages are the following: (1) they combine information from both time-domain and frequency-domain and, (2) they are also very flexible and do not make strong assumptions concerning the data generating process for the series under investigation.
Book Synopsis Wavelet Analysis of Financial Time Series by : Rabeh Khalfaoui
Download or read book Wavelet Analysis of Financial Time Series written by Rabeh Khalfaoui and published by . This book was released on 2012 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis deals with the contribution of wavelet methods on modeling economic and financial time series and consists of two parts: the univariate time series and multivariate time series. In the first part (chapters 2 and 3), we adopt univariate case. First, we examine the class of non-stationary long memory processes. A simulation study is carried out in order to compare the performance of some semi-parametric estimation methods for fractional differencing parameter. We also examine the long memory in volatility using FIGARCH models to model energy data. Results show that the Exact local Whittle estimation method of Shimotsu and Phillips [2005] is the better one and the oil volatility exhibit strong evidence of long memory. Next, we analyze the market risk of univariate stock market returns which is measured by systematic risk (beta) at different time horizons. Results show that beta is not stable, due to multi-trading strategies of investors. Results based on VaR analysis show that risk is more concentrated at higher frequency. The second part (chapters 4 and 5) deals with estimation of the conditional variance and correlation of multivariate time series. We consider two classes of time series: the stationary time series (returns) and the non-stationary time series (levels). We develop a novel approach, which combines wavelet multi-resolution analysis and multivariate GARCH models, i.e. the wavelet-based multivariate GARCH approach. However, to evaluate the volatility forecasts we compare the performance of several multivariate models using some criteria, such as loss functions, VaR estimation and hedging strategies.
Book Synopsis ANALYSIS OF FINANCIAL TIME SERIES, 2ND ED by : Ruey S. Tsay
Download or read book ANALYSIS OF FINANCIAL TIME SERIES, 2ND ED written by Ruey S. Tsay and published by . This book was released on 2009-01-01 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: Market_Desc: Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance Special Features: · Timely topics and recent results include: Value at Risk (VaR); high-frequency financial data analysis; MCMC methods; derivative pricing using jump diffusion with closed-form formulas; VaR calculation using extreme value theory based on nonhomogeneous two-dimensional Poisson process; and multivariate volatility models with time-varying correlations.· New topics to this edition include: Finmetrics in S-plus; estimation of stochastic diffusion equations for derivative pricing; use of realized volatilities; state=space model; and Kalman filter.· The second edition also includes new developments in financial econometrics and more examples of applications in finance.· Emphasis is placed on empirical financial data.· Chapter exercises have been increased in an effort to further reinforce the methods and applications in the text. About The Book: This book provides a comprehensive and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series, and gain experience in financial applications of various econometric methods.
Book Synopsis Introduction to Modern Time Series Analysis by : Gebhard Kirchgässner
Download or read book Introduction to Modern Time Series Analysis written by Gebhard Kirchgässner and published by Springer Science & Business Media. This book was released on 2012-10-08 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.
Book Synopsis Wavelet Applications in Economics and Finance by : Marco Gallegati
Download or read book Wavelet Applications in Economics and Finance written by Marco Gallegati and published by Springer. This book was released on 2014-08-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the application of wavelet and spectral methods for the analysis of nonlinear and dynamic processes in economics and finance. It reflects some of the latest developments in the area of wavelet methods applied to economics and finance. The topics include business cycle analysis, asset prices, financial econometrics, and forecasting. An introductory paper by James Ramsey, providing a personal retrospective of a decade's research on wavelet analysis, offers an excellent overview over the field.
