Author: Marcus J. Chambers
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 35
Book Description
Gaussian Estimation of Temporally Aggregated Cointegrated Systems
Author: Marcus J. Chambers
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 35
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 35
Book Description
Frequency Domain Gaussian Estimation of Temporally Aggregated Cointegrated Systems
Author: Marcus J. Chambers
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Continuous Time Modeling in the Behavioral and Related Sciences
Author: Kees van Montfort
Publisher: Springer
ISBN: 3319772198
Category : Medical
Languages : en
Pages : 442
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.
Publisher: Springer
ISBN: 3319772198
Category : Medical
Languages : en
Pages : 442
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.
The Estimation of cointegrating vectors with temporally aggregated time series
Author: Gabriel Pons Rotger
Publisher:
ISBN:
Category :
Languages : en
Pages : 208
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 208
Book Description
Journal of Economic Dynamics & Control
Author:
Publisher:
ISBN:
Category : Economic development
Languages : en
Pages : 964
Book Description
Publisher:
ISBN:
Category : Economic development
Languages : en
Pages : 964
Book Description
Temporal Disaggregation, Missing Observations, Outliers, and Forecasting
Author: Massimiliano Marcellino
Publisher:
ISBN:
Category : Automatic data collection systems
Languages : en
Pages : 44
Book Description
Publisher:
ISBN:
Category : Automatic data collection systems
Languages : en
Pages : 44
Book Description
Temporal Aggregation of GARCH Models
Author: Thomas Breuer
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
Book Description
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.
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
Book Description
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.
Some Consequences of Temporal Aggregation of a VARIMA Process
Author: Massimiliano Marcellino
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 60
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 60
Book Description
Bibliographie der Wirtschaftswissenschaften
Author:
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 946
Book Description
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 946
Book Description
The Effect of Temporal Aggregation on Discrete Dynamic Time Series Models
Author: William W. S. Wei
Publisher:
ISBN:
Category :
Languages : en
Pages : 342
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 342
Book Description