Long Memory In Economics
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Long Memory In Economics
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Author : Gilles Teyssière
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-22
Long Memory In Economics written by Gilles Teyssière and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-22 with Business & Economics categories.
Assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; and models from economic theory providing plausible micro foundations for the occurrence of long memory in economics.
Long Memory In Economics
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Author : Gilles Teyssière
language : en
Publisher: Springer
Release Date : 2009-09-02
Long Memory In Economics written by Gilles Teyssière and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-02 with Business & Economics categories.
Time Series With Long Memory
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Author : Peter M. Robinson
language : en
Publisher: Advanced Texts in Econometrics
Release Date : 2003
Time Series With Long Memory written by Peter M. Robinson and has been published by Advanced Texts in Econometrics this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.
Long memory time series are characterized by a strong dependence between distant events.
Economic Dynamics With Memory
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Author : Vasily E. Tarasov
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2021-01-18
Economic Dynamics With Memory written by Vasily E. Tarasov and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-18 with Business & Economics categories.
This book presents the applications of fractional calculus, fractional operators of non-integer orders and fractional differential equations in describing economic dynamics with long memory. Generalizations of basic economic concepts, notions and methods for the economic processes with memory are suggested. New micro and macroeconomic models with continuous time are proposed to describe the fractional economic dynamics with long memory as well.
Long Memory In The Volatility Of Indian Financial Market
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Author : Dilip Kumar
language : en
Publisher:
Release Date : 2014-02
Long Memory In The Volatility Of Indian Financial Market written by Dilip Kumar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02 with categories.
Professorial Dissertation from the year 2014 in the subject Business economics - Investment and Finance, grade: A, language: English, abstract: This book examines the long memory characteristics in the volatility of the Indian stock market, the Indian exchange rates and the Indian banking sector. This book also reviews the chain of approaches to estimate the long memory parameter. The long memory characteristics of the financial time series are widely studied and have implications for various economics and finance theories. The most important financial implication is related to the violation of the weak-form of market efficiency which encourages the traders, investors and portfolio managers to develop models for making predictions and to construct and implement speculative trading and investment strategies. In an efficient market, the price of an asset should follow a random walk process in which the price change is unaffected by its lagged price changes and has no memory.
Long Memory Processes
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Author : Jan Beran
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-05-14
Long Memory Processes written by Jan Beran and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-14 with Mathematics categories.
Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.
Long Memory Time Series
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Author : Wilfredo Palma
language : en
Publisher: John Wiley & Sons
Release Date : 2007-04-27
Long Memory Time Series written by Wilfredo Palma and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-27 with Mathematics categories.
A self-contained, contemporary treatment of the analysis of long-range dependent data Long-Memory Time Series: Theory and Methods provides an overview of the theory and methods developed to deal with long-range dependent data and describes the applications of these methodologies to real-life time series. Systematically organized, it begins with the foundational essentials, proceeds to the analysis of methodological aspects (Estimation Methods, Asymptotic Theory, Heteroskedastic Models, Transformations, Bayesian Methods, and Prediction), and then extends these techniques to more complex data structures. To facilitate understanding, the book: Assumes a basic knowledge of calculus and linear algebra and explains the more advanced statistical and mathematical concepts Features numerous examples that accelerate understanding and illustrate various consequences of the theoretical results Proves all theoretical results (theorems, lemmas, corollaries, etc.) or refers readers to resources with further demonstration Includes detailed analyses of computational aspects related to the implementation of the methodologies described, including algorithm efficiency, arithmetic complexity, CPU times, and more Includes proposed problems at the end of each chapter to help readers solidify their understanding and practice their skills A valuable real-world reference for researchers and practitioners in time series analysis, economerics, finance, and related fields, this book is also excellent for a beginning graduate-level course in long-memory processes or as a supplemental textbook for those studying advanced statistics, mathematics, economics, finance, engineering, or physics. A companion Web site is available for readers to access the S-Plus and R data sets used within the text.
Testing Stationary Nonnested Short Memory Against Long Memory Processes
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Author : Paramsothy Silvapulle
language : en
Publisher: La Trobe University Schools of Economics and Commerce
Release Date : 1995
Testing Stationary Nonnested Short Memory Against Long Memory Processes written by Paramsothy Silvapulle and has been published by La Trobe University Schools of Economics and Commerce this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Business & Economics categories.
Large Sample Inference For Long Memory Processes
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Author : Donatas Surgailis
language : en
Publisher: World Scientific Publishing Company
Release Date : 2012-04-27
Large Sample Inference For Long Memory Processes written by Donatas Surgailis and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-27 with Mathematics categories.
Box and Jenkins (1970) made the idea of obtaining a stationary time series by differencing the given, possibly nonstationary, time series popular. Numerous time series in economics are found to have this property. Subsequently, Granger and Joyeux (1980) and Hosking (1981) found examples of time series whose fractional difference becomes a short memory process, in particular, a white noise, while the initial series has unbounded spectral density at the origin, i.e. exhibits long memory.Further examples of data following long memory were found in hydrology and in network traffic data while in finance the phenomenon of strong dependence was established by dramatic empirical success of long memory processes in modeling the volatility of the asset prices and power transforms of stock market returns.At present there is a need for a text from where an interested reader can methodically learn about some basic asymptotic theory and techniques found useful in the analysis of statistical inference procedures for long memory processes. This text makes an attempt in this direction. The authors provide in a concise style a text at the graduate level summarizing theoretical developments both for short and long memory processes and their applications to statistics. The book also contains some real data applications and mentions some unsolved inference problems for interested researchers in the field./a
Long Term Memory In Stock Market Prices
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Author : Andrew Wen-Chuan Lo
language : en
Publisher:
Release Date : 1989
Long Term Memory In Stock Market Prices written by Andrew Wen-Chuan Lo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Economics categories.
A test for long-run memory that is robust to short-range dependence is developed. It is a simple extension of Mandelbrot's "range over standard deviation" or R/S statistic, for which the relevant asymptotic sampling theory is derived via functional central limit theory. This test is applied to daily, weekly, monthly, and annual stock returns indexes over several different time periods. Contrary to previous findings, there is no evidence of long-range dependence in any of the indexes over any sample period or sub-period once short-term autocorrelations are taken into account. Illustrative Monte Carlo experiments indicate that the modified R/S test has power against at least two specific models of long-run memory, suggesting that stochastic models of short-range dependence may adequately capture the time series behavior of stock returns