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New Introduction To Multiple Time Series Analysis


New Introduction To Multiple Time Series Analysis
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New Introduction To Multiple Time Series Analysis


New Introduction To Multiple Time Series Analysis
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Author : Helmut Lütkepohl
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-26

New Introduction To Multiple Time Series Analysis written by Helmut Lütkepohl 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 2007-07-26 with Business & Economics categories.


This is the new and totally revised edition of Lütkepohl’s classic 1991 work. It provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models. The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it.



Introduction To Multiple Time Series Analysis


Introduction To Multiple Time Series Analysis
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Author : Helmut Lütkepohl
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Introduction To Multiple Time Series Analysis written by Helmut Lütkepohl 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 2013-04-17 with Business & Economics categories.




Economic Forecasts


Economic Forecasts
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Author : Ralf Brüggemann
language : en
Publisher: Lucius & Lucius DE
Release Date : 2011

Economic Forecasts written by Ralf Brüggemann and has been published by Lucius & Lucius DE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.


No detailed description available for "Economic Forecasts".



Multivariate Time Series Analysis And Applications


Multivariate Time Series Analysis And Applications
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Author : William W. S. Wei
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-18

Multivariate Time Series Analysis And Applications written by William W. S. Wei 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 2019-03-18 with Mathematics categories.


An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.



Advances In Time Series Analysis And Forecasting


Advances In Time Series Analysis And Forecasting
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Author : Ignacio Rojas
language : en
Publisher: Springer
Release Date : 2017-07-31

Advances In Time Series Analysis And Forecasting written by Ignacio Rojas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-31 with Business & Economics categories.


This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.



State Space Methods For Time Series Analysis


State Space Methods For Time Series Analysis
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Author : Jose Casals
language : en
Publisher: CRC Press
Release Date : 2018-09-03

State Space Methods For Time Series Analysis written by Jose Casals and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Mathematics categories.


The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors’ E4 MATLAB® toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.



Ageing Population Risks


Ageing Population Risks
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Author : Pavel Shevchenko
language : en
Publisher: MDPI
Release Date : 2018-08-09

Ageing Population Risks written by Pavel Shevchenko and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-09 with Business & Economics categories.


This book is a printed edition of the Special Issue "Ageing Population Risks" that was published in Risks



Essays In Honor Of Joon Y Park


Essays In Honor Of Joon Y Park
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Author : Yoosoon Chang
language : en
Publisher: Emerald Group Publishing
Release Date : 2023-04-24

Essays In Honor Of Joon Y Park written by Yoosoon Chang and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-24 with Business & Economics categories.


Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.



Financial Signal Processing And Machine Learning


Financial Signal Processing And Machine Learning
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Author : Ali N. Akansu
language : en
Publisher: John Wiley & Sons
Release Date : 2016-05-31

Financial Signal Processing And Machine Learning written by Ali N. Akansu 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 2016-05-31 with Technology & Engineering categories.


The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.



Advances In Intelligent Data Analysis Xiii


Advances In Intelligent Data Analysis Xiii
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Author : Hendrik Blockeel
language : en
Publisher: Springer
Release Date : 2014-10-24

Advances In Intelligent Data Analysis Xiii written by Hendrik Blockeel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-24 with Computers categories.


This book constitutes the refereed conference proceedings of the 13th International Conference on Intelligent Data Analysis, which was held in October/November 2014 in Leuven, Belgium. The 33 revised full papers together with 3 invited papers were carefully reviewed and selected from 70 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.