On detecting and modeling periodic correlation in financial data

Ewa Broszkiewicz-Suwaj, Andrzej Makagon, Rafał Weron and Agnieszka Wyłomańska
Additional contact information
Ewa Broszkiewicz-Suwaj: Wroclaw University of Technology
Andrzej Makagon: Hampton University

Econometrics from University Library of Munich, Germany

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.

Keywords: periodic correlation; sample coherence; electricity price; periodic autoregression; vector autoregression (search for similar items in EconPapers)
JEL-codes: C22 C32 L94 Q40 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2005-02-07
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: Type of Document - pdf; pages: 12. Appeared in: Physica A 336 (2004) pp. 196-205
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Journal Article: On detecting and modeling periodic correlation in financial data (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0502006

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