Author: J. Isaac Miller
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: William W. S. Wei
Publisher: John Wiley & Sons
ISBN: 1119502853
Category : Mathematics
Languages : en
Pages : 536

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Book Description
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.

Author: Eric Ghysels
Publisher:
ISBN:
Category : Cointegration
Languages : en
Pages : 44

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Book Description
We examine the effects of mixed sampling frequencies and temporal aggregation on standard tests for cointegration. We find that the effects of aggregation on the size of the tests may be severe. Matching sampling schemes of all series generally reduces size, and the nominal size is obtained when all series are skip sampled in the same way. When matching all schemes is not feasible, but when some high-frequency data are available, we show how to use mixed-frequency models to improve the size distortion of the tests. We test stock prices and dividends for cointegration as an empirical demonstration.

Author: Erik Hjalmarsson
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 40

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Book Description
Methods of inference based on a unit root assumption in the data are typically not robust to even small deviations from this assumption. In this paper, we propose robust procedures for a residual-based test of cointegration when the data are generated by a near unit root process. A Bonferroni method is used to address the uncertainty regarding the exact degree of persistence in the process. We thus provide a method for valid inference in multivariate near unit root processes where standard cointegration tests may be subject to substantial size distortions and standard OLS inference may lead to spurious results. Empirical illustrations are given by: (i) a re-examination of the Fisher hypothesis, and (ii) a test of the validity of the cointegrating relationship between aggregate consumption, asset holdings, and labor income, which has attracted a great deal of attention in the recent finance literature.

Author: Alfred A. Haug
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
The effect of time-aggregation on the power of commonly used tests for cointegration is studied with the Monte Carlo method. The results suggest that, for a given span, a higher frequency of observation can add substantially to test power. Also, Engle and Granger's (1987) ADF test leads overall to the highest and most stable powers for typical finite sample sizes and likely data generating processes encountered by practitioners.

Author: Nlandu Mamingi
Publisher:
ISBN:
Category :
Languages : en
Pages : 44

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Author: Pierre Perron
Publisher:
ISBN:
Category : Cointegration
Languages : en
Pages : 46

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Author: Ya-Hue Lee
Publisher:
ISBN:
Category : Cointegration
Languages : en
Pages : 260

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Author: Erik Hjalmarsson
Publisher: International Monetary Fund
ISBN:
Category : Business & Economics
Languages : en
Pages : 28

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Book Description
We investigate the properties of Johansen's (1988, 1991) maximum eigenvalue and trace tests for cointegration under the empirically relevant situation of near-integrated variables. Using Monte Carlo techniques, we show that in a system with near-integrated variables, the probability of reaching an erroneous conclusion regarding the cointegrating rank of the system is generally substantially higher than the nominal size. The risk of concluding that completely unrelated series are cointegrated is therefore non-negligible. The spurious rejection rate can be reduced by performing additional tests of restrictions on the cointegrating vector(s), although it is still substantially larger than the nominal size.

Author: Elena Pesavento
Publisher:
ISBN:
Category : Cointegration
Languages : en
Pages : 308

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