Modelling Non-Stationary Economic Time Series, S. Burke; J. Hunter

Автор: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243312 ISBN-13(EAN): 9780230243316
Издательство: Springer
Цена: 55890 T
Описание: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521139813 ISBN-13(EAN): 9780521139816
Издательство: Cambridge Academ
Рейтинг:
Цена: 78150.00 T
Наличие на складе: Ожидается поступление.
Описание: This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation.

Название: The Econometric Modelling of Financial Time Series
ISBN: 0521624924 ISBN-13(EAN): 9780521624923
Издательство: Cambridge Academ
Рейтинг:
Цена: 28500.00 T
Наличие на складе: Невозможна поставка.
Описание: Substantially revised and updated second edition of Terry Mills' best-selling graduate textbook The Econometric Modelling of Financial Time Series. The book provides detailed coverage of the variety of models that are currently being used in the empiric

Автор: Terence C. Mills
Название: The Econometric Modelling of Financial Time Series
ISBN: 052171009X ISBN-13(EAN): 9780521710091
Издательство: Cambridge Academ
Рейтинг:
Цена: 49630.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This best-selling graduate textbook provides detailed coverage of the latest research techniques and findings relating to the empirical analysis of financial markets. This third edition contains a wealth of material reflecting the developments of the last decade, including a new chapter on nonlinearity and its testing.

Автор: Franses
Название: Time Series Models for Business and Economic Forecasting
ISBN: 0521817706 ISBN-13(EAN): 9780521817707
Издательство: Cambridge Academ
Рейтинг:
Цена: 99270.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With a new author team contributing decades of practical experience, this fully updated second edition textbook summarises the most critical decisions, techniques and steps in creating effective forecasting models. Includes all new theoretical and practical exercises geared at guiding students through the steps of creating forecasting models on their own.

Автор: Bell
Название: Economic Time Series
ISBN: 143984657X ISBN-13(EAN): 9781439846575
Издательство: Taylor&Francis
Рейтинг:
Цена: 132710.00 T
Наличие на складе: Невозможна поставка.
Описание: Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time series modeling and seasonal adjustment, as is reflected both in the contents of the chapters and in their authorship, with contributors coming from academia and government statistical agencies. For easier perusal and absorption, the contents have been grouped into seven topical sections: Section I deals with periodic modeling of time series, introducing, applying, and comparing various seasonally periodic models Section II examines the estimation of time series components when models for series are misspecified in some sense, and the broader implications this has for seasonal adjustment and business cycle estimation Section III examines the quantification of error in X-11 seasonal adjustments, with comparisons to error in model-based seasonal adjustments Section IV discusses some practical problems that arise in seasonal adjustment: developing asymmetric trend-cycle filters, dealing with both temporal and contemporaneous benchmark constraints, detecting trading-day effects in monthly and quarterly time series, and using diagnostics in conjunction with model-based seasonal adjustment Section V explores outlier detection and the modeling of time series containing extreme values, developing new procedures and extending previous work Section VI examines some alternative models and inference procedures for analysis of seasonal economic time series Section VII deals with aspects of modeling, estimation, and forecasting for nonseasonal economic time series By presenting new methodological developments as well as pertinent empirical analyses and reviews of established methods, the book provides much that is stimulating and practically useful for the serious researcher and analyst of economic time series.

Автор: Terence C. Mills
Название: The Econometric Modelling of Financial Time Series
ISBN: 0521883814 ISBN-13(EAN): 9780521883818
Издательство: Cambridge Academ
Цена: 70750.00 T
Наличие на складе: Невозможна поставка.
Описание: A unique, self-contained introduction to nonequilibrium many-body theory, with a focus on the time-dependent aspect. Topics range from basic quantum mechanics to nonequilibrium Green`s function formalisms, and with full derivations of every result and an abundance of illustrative examples, this accessible book is ideal for graduate students and researchers alike.

Автор: I.B. MacNeill; G. Umphrey
Название: Time Series and Econometric Modelling
ISBN: 9401086249 ISBN-13(EAN): 9789401086240
Издательство: Springer
Рейтинг:
Цена: 139750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: On May 27-31, 1985, a series of symposia was held at The University of Western Ontario, London, Canada, to celebrate the 70th birthday of Pro- fessor V.

Автор: Granger Clive William John, Hatanaka Michio, Granger C. W. J.
Название: Spectral Analysis of Economic Time Series. (Psme-1)
ISBN: 069162478X ISBN-13(EAN): 9780691624785
Издательство: Wiley
Рейтинг:
Цена: 44350.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for time series data. New methods for analyzing series containing no trends have been developed by communication engineering, and much recent research has been devoted to adapting and extending these methods so that

Автор: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243304 ISBN-13(EAN): 9780230243309
Издательство: Springer
Рейтинг:
Цена: 186330.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.

Автор: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243312 ISBN-13(EAN): 9780230243316
Издательство: Springer
Рейтинг:
Цена: 55890.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.

Автор: S. Burke; J. Hunter
Название: Modelling Non-Stationary Economic Time Series
ISBN: 140390202X ISBN-13(EAN): 9781403902023
Издательство: Springer
Рейтинг:
Цена: 102480.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of econometrics to real world problems.

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521196604 ISBN-13(EAN): 9780521196604
Издательство: Cambridge Academ
Рейтинг:
Цена: 109830.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation.