Statistics for Long-Memory Processes

Statistics for Long-Memory Processes PDF Author: Jan Beran
Publisher: Routledge
ISBN: 1351414119
Category : Mathematics
Languages : en
Pages : 315

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Book Description
Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations, statistical methods, and applications. The material emphasizes basic principles and practical applications and provides an integrated perspective of both theory and practice. This book explores data sets from a wide range of disciplines, such as hydrology, climatology, telecommunications engineering, and high-precision physical measurement. The data sets are conveniently compiled in the index, and this allows readers to view statistical approaches in a practical context. Statistical Methods for Long Term Memory Processes also supplies S-PLUS programs for the major methods discussed. This feature allows the practitioner to apply long memory processes in daily data analysis. For newcomers to the area, the first three chapters provide the basic knowledge necessary for understanding the remainder of the material. To promote selective reading, the author presents the chapters independently. Combining essential methodologies with real-life applications, this outstanding volume is and indispensable reference for statisticians and scientists who analyze data with long-range dependence.

Statistics for Long-Memory Processes

Statistics for Long-Memory Processes PDF Author: Jan Beran
Publisher: Routledge
ISBN: 1351414119
Category : Mathematics
Languages : en
Pages : 315

Get Book Here

Book Description
Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations, statistical methods, and applications. The material emphasizes basic principles and practical applications and provides an integrated perspective of both theory and practice. This book explores data sets from a wide range of disciplines, such as hydrology, climatology, telecommunications engineering, and high-precision physical measurement. The data sets are conveniently compiled in the index, and this allows readers to view statistical approaches in a practical context. Statistical Methods for Long Term Memory Processes also supplies S-PLUS programs for the major methods discussed. This feature allows the practitioner to apply long memory processes in daily data analysis. For newcomers to the area, the first three chapters provide the basic knowledge necessary for understanding the remainder of the material. To promote selective reading, the author presents the chapters independently. Combining essential methodologies with real-life applications, this outstanding volume is and indispensable reference for statisticians and scientists who analyze data with long-range dependence.

Handling Complexity in Learning Environments

Handling Complexity in Learning Environments PDF Author: Jan Elen
Publisher: Emerald Group Publishing
ISBN: 0080449867
Category : Education
Languages : en
Pages : 329

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Book Description
Offers an analysis of complexity in learning environments from a cognitive perspective. This book makes specific suggestions for educational practice on complexity. It discusses theoretical accounts and empirical findings about learning, the learner, and learning environments.

Parameter Estimation in Stochastic Volatility Models

Parameter Estimation in Stochastic Volatility Models PDF Author: Jaya P. N. Bishwal
Publisher: Springer Nature
ISBN: 3031038614
Category : Mathematics
Languages : en
Pages : 634

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Book Description
This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.

Prediction and Causality in Econometrics and Related Topics

Prediction and Causality in Econometrics and Related Topics PDF Author: Nguyen Ngoc Thach
Publisher: Springer Nature
ISBN: 303077094X
Category : Technology & Engineering
Languages : en
Pages : 691

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Book Description
This book provides the ultimate goal of economic studies to predict how the economy develops—and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques—including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy. This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.

Commodity Modeling and Pricing

Commodity Modeling and Pricing PDF Author: Peter V. Schaeffer
Publisher: John Wiley & Sons
ISBN: 047031723X
Category : Business & Economics
Languages : en
Pages : 345

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Book Description
Commodity Modeling and Pricing provides extensions and applications of state-of-the-art methods for analyzing resource commodity behavior. Drawing from the seminal work of Professor Walter Labys on the development of econometric methods for forecasting commodity prices, this collection of essays features expert contributors ranging from practitioners in private industry, public sector, and nongovernmental organizations to scholars in higher education–all of whom were Labys's former students or collaborators. Filled with in-depth insights and expert advice, Commodity Modeling and Pricing contains the information you need to excel in this demanding environment.

Topics in Advanced Econometrics

Topics in Advanced Econometrics PDF Author: Herman J. Bierens
Publisher: Cambridge University Press
ISBN: 9780521565110
Category : Business & Economics
Languages : en
Pages : 274

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Book Description
A rigorous treatment of a number of timely topics in advanced econometrics.

Issues in General Economic Research and Application: 2013 Edition

Issues in General Economic Research and Application: 2013 Edition PDF Author:
Publisher: ScholarlyEditions
ISBN: 149010688X
Category : Business & Economics
Languages : en
Pages : 1229

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Book Description
Issues in General Economic Research and Application: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Theoretical Economics. The editors have built Issues in General Economic Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Theoretical Economics in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in General Economic Research and Application: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Models for Long Memory and High Frequency Financial Time Series

Models for Long Memory and High Frequency Financial Time Series PDF Author: Young Wook Han
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 328

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Book Description


Time Series and Panel Data Econometrics

Time Series and Panel Data Econometrics PDF Author: M. Hashem Pesaran
Publisher: Oxford University Press
ISBN: 0198736916
Category : Business & Economics
Languages : en
Pages : 1095

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Book Description
This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.

Stochastic Volatility

Stochastic Volatility PDF Author: Neil Shephard
Publisher: Oxford University Press, USA
ISBN: 0199257205
Category : Business & Economics
Languages : en
Pages : 534

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Book Description
Stochastic volatility is the main concept used in the fields of financial economics and mathematical finance to deal with time-varying volatility in financial markets. This work brings together some of the main papers that have influenced this field, andshows that the development of this subject has been highly multidisciplinary.