Advanced Search
MyIDEAS: Login to save this paper or follow this series

The Spatial Analysis of Time Series

Contents:

Author Info

  • Joon Y. Park

Abstract

In this paper, we propose a method of analyzing time series in the spatial domain. The analysis is based on the inference on the local time and its expectation. Both for the stationary and nonstationary time series, the spatial distributions are provided by the local time, and some of their important characteristics can be examined through the investigation of the expected local time. The methodology developed in the paper for the analysis of the expected local time applies to both stationary and nonstationary time series. The expected local time, however, reduces to the density of the time invariant distribution if the underlying time series is stationary. Our analysis may therefore be regarded as an extension to the nonstationary time series of the usual distributional analysis for the stationary time series. Our approach is nonparametric, and imposes very weak and minimal conditions on the underlying time series. In particular, we allow for observations generated from a wide class of stochastic processes with stationary and mixing increments, or general markov processes including virtually all diffusion models used in practice. Proposed are several interesting applications of our methodology, such as forecast of spatial distribution, test of structural break in spatial domain, specification test in spatial domain, test of equality in spatial distribution and test of spatial dominance

Download Info

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society 2004 North American Winter Meetings with number 595.

as in new window
Length:
Date of creation: 11 Aug 2004
Date of revision:
Handle: RePEc:ecm:nawm04:595

Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Email:
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC

Related research

Keywords: local time; expected local time; semimartingale; markov process; diffusion; bootstrap; sub-sampling.;

Other versions of this item:

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Federico M. Bandi & Peter C.B. Phillips, 2001. "Fully Nonparametric Estimation of Scalar Diffusion Models," Cowles Foundation Discussion Papers 1332, Cowles Foundation for Research in Economics, Yale University.
  2. Oliver Linton & Esfandiar Maasoumi & Whang, Yoon-Jae, 2002. "Consistent Testing for Stochastic Dominance: A Subsampling Approach," Cowles Foundation Discussion Papers 1356, Cowles Foundation for Research in Economics, Yale University, revised Mar 2002.
  3. Bandi, Federico M., 2002. "Short-term interest rate dynamics: a spatial approach," Journal of Financial Economics, Elsevier, vol. 65(1), pages 73-110, July.
  4. Carr, Peter P & Jarrow, Robert A, 1990. "The Stop-Loss Start-Gain Paradox and Option Valuation: A New Decomposition into Intrinsic and Time Value," Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 469-92.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Qiying Wang & Peter C.B. Phillips, 2006. "Asymptotic Theory for Local Time Density Estimation and Nonparametric Cointegrating Regression," Cowles Foundation Discussion Papers 1594, Cowles Foundation for Research in Economics, Yale University.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:ecm:nawm04:595. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.