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

On detecting and modeling periodic correlation in financial data

Contents:

Author Info

  • Ewa Broszkiewicz-Suwaj

    (Wroclaw University of Technology)

  • Andrzej Makagon

    (Hampton University)

  • Rafal Weron

    (Hugo Steinhaus Center)

  • Agnieszka Wylomanska

    (Wroclaw University of Technology)

Abstract

For many economic problems standard statistical analysis, based on the notion of stationarity, is not adequate. These include modeling seasonal decisions of consumers, forecasting business cycles and - as we show in the present article - modeling wholesale power market prices. We apply standard methods and a novel spectral domain technique to conclude that electricity price returns exhibit periodic correlation with daily and weekly periods. As such they should be modeled with periodically correlated processes. We propose to apply periodic autoregression (PAR) models which are closely related to the standard instruments in econometric analysis - vector autoregression (VAR) models.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://128.118.178.162/eps/em/papers/0502/0502006.pdf
Download Restriction: no

Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0502006.

as in new window
Length: 12 pages
Date of creation: 07 Feb 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0502006

Note: Type of Document - pdf; pages: 12. Appeared in: Physica A 336 (2004) pp. 196-205
Contact details of provider:
Web page: http://128.118.178.162

Related research

Keywords: periodic correlation; sample coherence; electricity price; periodic autoregression; vector autoregression;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

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

Cited by:
  1. Ewa Broszkiewicz-Suwaj & Agnieszka Wylomanska, 2004. "Periodic correlation vs. integration and cointegration (Okresowa korelacja a integracja i kointegracja)," HSC Research Reports HSC/04/04, Hugo Steinhaus Center, Wroclaw University of Technology.
  2. Mestekemper, Thomas & Kauermann, Göran & Smith, Michael S., 2013. "A comparison of periodic autoregressive and dynamic factor models in intraday energy demand forecasting," International Journal of Forecasting, Elsevier, vol. 29(1), pages 1-12.

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:wpa:wuwpem:0502006. 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: (EconWPA).

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.