Gaussian Estimation of Temporally Aggregated Cointegrated Systems PDF Download
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Author: Marcus J. Chambers
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 35
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Author: Marcus J. Chambers
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 35
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Book Description
Author: Marcus J. Chambers
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Kees van Montfort
Publisher: Springer
ISBN: 3319772198
Category : Medical
Languages : en
Pages : 442
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Book Description
This unique book provides an overview of continuous time modeling in the behavioral and related sciences. It argues that the use of discrete time models for processes that are in fact evolving in continuous time produces problems that make their application in practice highly questionable. One main issue is the dependence of discrete time parameter estimates on the chosen time interval, which leads to incomparability of results across different observation intervals. Continuous time modeling by means of differential equations offers a powerful approach for studying dynamic phenomena, yet the use of this approach in the behavioral and related sciences such as psychology, sociology, economics and medicine, is still rare. This is unfortunate, because in these fields often only a few discrete time (sampled) observations are available for analysis (e.g., daily, weekly, yearly, etc.). However, as emphasized by Rex Bergstrom, the pioneer of continuous-time modeling in econometrics, neither human beings nor the economy cease to exist in between observations. In 16 chapters, the book addresses a vast range of topics in continuous time modeling, from approaches that closely mimic traditional linear discrete time models to highly nonlinear state space modeling techniques. Each chapter describes the type of research questions and data that the approach is most suitable for, provides detailed statistical explanations of the models, and includes one or more applied examples. To allow readers to implement the various techniques directly, accompanying computer code is made available online. The book is intended as a reference work for students and scientists working with longitudinal data who have a Master's- or early PhD-level knowledge of statistics.
Author: Gabriel Pons Rotger
Publisher:
ISBN:
Category :
Languages : en
Pages : 208
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Author:
Publisher:
ISBN:
Category : Economic development
Languages : en
Pages : 964
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Author: Massimiliano Marcellino
Publisher:
ISBN:
Category : Automatic data collection systems
Languages : en
Pages : 44
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Author: Thomas Breuer
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
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We examine the properties of temporally aggregated distributions when one period changes follow a strong GARCH process. Our main results: (1) We derive explicit expressions for the conditional volatility and kurtosis of the aggregated distribution. (2) As the time horizon gets longer the conditional aggregated kurtosis approaches three (resp. a different constant, for stock variables) or infinity depending on whether or not a simple inequality in term of the GARCH parameters is satisfied. (3) Given that the aggregation of a strong GARCH process is not any more a strong GARCH process, the question arises for which data frequency a description by a strong GARCH process fits the data best. We propose a quasi maximum likelihood method to determine the optimal data frequency for a GARCH description. (4) For models with different basic frequency and with different residual distributions we perform out of sample tests of three months density forecasts on the basis of daily market prices. It turns out that low frequency models with longer basic periods and fewer aggregation steps fare better than high frequency models. This seems to imply that for high frequency models the advantage of having more data available for estimation is outweighed by the disadvantage of aggregation magnifying estimation errors.
Author: Massimiliano Marcellino
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 60
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Author:
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 946
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Author: William W. S. Wei
Publisher:
ISBN:
Category :
Languages : en
Pages : 342
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