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Author: Agustín Maravall
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages : 52
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Book Description
Author: Agustín Maravall
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages : 52
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 34
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Book Description
Author: Agustâ ̧n Maravall
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Agustín Maravall
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages : 236
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Book Description
Author: Agustín Maravall
Publisher:
ISBN:
Category :
Languages : en
Pages : 34
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Book Description
Author: Agustín Maravall
Publisher:
ISBN:
Category :
Languages : de
Pages : 34
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Book Description
Author: Víctor Gómez
Publisher:
ISBN:
Category :
Languages : en
Pages : 34
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Book Description
Author: Haim Y. Bleikh
Publisher: CRC Press
ISBN: 1317010175
Category : Business & Economics
Languages : en
Pages : 148
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Book Description
In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and financial institutions and provide statistics to whomsoever requires them. Such analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory and focused on modelling. An understanding of time series and the application and understanding of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. Dealing with economic data involves grappling with things like varying numbers of working and trading days in different months and movable national holidays. Special attention has to be given to such things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover hidden patterns in the data and then to generate accurate forecasts. The case studies in this book demonstrate that time series adjustment methods can be efficaciously applied and utilized, for both analysis and forecasting, but they must be used in the context of reasoned statistical and economic judgment. The authors believe this is the first published study to really deal with this issue of context.
Author: Eric Ghysels
Publisher: Cambridge University Press
ISBN: 9780521565882
Category : Business & Economics
Languages : en
Pages : 258
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Book Description
Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.
Author: Estela Bee Dagum
Publisher: Springer
ISBN: 3319318225
Category : Business & Economics
Languages : en
Pages : 293
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Book Description
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
